**Rehabilitation Strategies for Patients with Femoral Neck Fractures in Sarcopenia: A Narrative Review**

**Marianna Avola <sup>1</sup> , Giulia Rita Agata Mangano <sup>1</sup> , Gianluca Testa 2,\* , Sebastiano Mangano <sup>2</sup> , Andrea Vescio <sup>2</sup> , Vito Pavone <sup>2</sup> and Michele Vecchio <sup>1</sup>**


Received: 10 August 2020; Accepted: 26 September 2020; Published: 26 September 2020

**Abstract:** Sarcopenia is defined as a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength. It has been identified as one of the most common comorbidities associated with femoral neck fracture (FNF). The aim of this review was to evaluate the impact of physical therapy on FNF patients' function and rehabilitation. The selected articles were randomized controlled trials (RCTs), published in the last 10 years. Seven full texts were eligible for this review: three examined the impact of conventional rehabilitation and nutritional supplementation, three evaluated the effects of rehabilitation protocols compared to new methods and a study explored the intervention with erythropoietin (EPO) in sarcopenic patients with FNF and its potential effects on postoperative rehabilitation. Physical activity and dietary supplementation are the basic tools of prevention and rehabilitation of sarcopenia in elderly patients after hip surgery. The most effective physical therapy seems to be exercise of progressive resistance. Occupational therapy should be included in sarcopenic patients for its importance in cognitive rehabilitation. Erythropoietin and bisphosphonates could represent medical therapy resources.

**Keywords:** sarcopenia; elderly; frailty; fractures; ageing fractures; complications; recovery; rehabilitation; nutritional supplements; physical therapy

#### **1. Introduction**

Sarcopenia is defined as a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, with risk of adverse outcomes such as physical disability, poor quality of life and death. [1] Prevalence of sarcopenia varies among age groups, geographic regions and evaluated context. Estimated prevalence is 1% to 29% in community-dwelling older people, 14% to 33% in longterm care and 10% in acute hospital care populations [2,3]. Starting from 40 years of age, each ten years, healthy adults lose approximately 8% of their muscle mass. Moreover, between 40 and 70 years old, healthy adults lose an average of 24% of muscle, which accelerates to 15% per decade past the age of 70. [4] The diagnosis of sarcopenia should be based on concomitant presence of low muscle mass and low muscle function [4,5].

The European Working Group on Sarcopenia in Older People (EWGSOP) defined sarcopenia as an acute or chronic disease based on low levels three measured parameters: muscle strength, muscle quantity/quality and physical performance, as an indicator of its severity [1,6].

Early sarcopenia is characterized by size reduction in muscle. Gradually, it also occurs as a decrease in the quality of muscle tissue, which leads to loss of functionality and fragility [7,8]. The assessment of sarcopenia requires objective measurements of muscle strength and muscle mass. Several methods of evaluation for sarcopenia considered walking speed, the circumference of the calf, the analysis of bioimpedance, grip strength and DEXA imaging methods. However, none of these measurements are sufficiently sensitive or specific [8–10]. Sarcopenia has been identified as one of the most common comorbidities associated with femoral neck fracture (FNF) patients [11]. Among these different comorbidities, apart from Sarcopenia, protein-energy malnutrition has been reported in 20 to 85 % of cases, depending on age and gender [12,13]. Besides the age-related loss of muscle mass, trauma mechanism, and consequent associated immobilization, cause negative adjustment in body composition. Bed confinement, and the reduced mobility of hospitalized older patients, are associated with loss of muscle mass, muscle function and bone mineral density from the 10th day, and up to two months, after the fracture [13,14]. During the first year from fracture, about 5–6% of muscle mass may be lost [15,16]. It was reported that 28% of patients who were outpatients before hip fracture were unable to walk 12 months after surgery, while as many as 25–30% of patients were unable to return to their previous situation. [16–18].

Treatment of sarcopenia is mainly nonpharmacological. First, an adequate nutrition to ensure the intake of micronutrients and macronutrients is needed. Calories should be 24 to 36 kcal/kg per day; a minimum daily protein intake of 1.0 g/kg body weight, up to 1.5 g spread equally over three meals and maintenance of serum vitamin D levels to 100 nmol/L (40 ng/mL) from vitamin D–rich diet or vitamin D supplementation. Supplementation with creatine monohydrate, antioxidants, amino acid metabolites, omega-3 fatty acids and other compounds are being studied [3]. A crucial role is played by physical activity, especially resistance training, which is the key element for increasing muscle strength and physical performance. Currently, the strategy of combined nutrition supplementation and exercise appears encouraging in the management of sarcopenia.

The aim of this review is to evaluate the impact of rehabilitation with or without other interventions, including nutritional supplementation and pharmacological therapy, on indicators of sarcopenia for FNF (femoral neck fracture) patients.

#### **2. Experimental Section**

#### *2.1. Literature Search Strategy*

To find clinical trials involving the rehabilitation of sarcopenia and FNF, two authors (M.A, G.R.A.M.) searched in three medical databases (PubMed, Cochrane Library and PEDro) during the month of June 2020. The terms used for the research were sarcopenia and hip fracture and rehabilitation.

#### *2.2. Selection Criteria*

The selected articles had to be published in the last 10 years, written in the English language and had to be randomized controlled trials (RCT), observational studies or cases reports published in peer reviewed journals. The authors excluded articles written in other languages, studies with no results or subjects involved and reviews about the topic. Papers with no accessible data, or no available full texts, were also excluded. M.A. and G.R.A.M. selected the studies independently, resolving any discrepancies about the selection by discussion. The senior investigator (M.V.) was consulted to revise the selection process.

#### **3. Results**

#### *3.1. Search Progress and Data Extraction*

A total of 74 articles were selected based on their titles. Excluding doubles, 63 articles were screened upon their titles. At the end of this screening, 14 abstracts were selected and read independently by the two authors. Five abstracts were excluded: three were not trials, two were reviews and one did not assess sarcopenia in the subjects studied. The authors screened and read eight full texts, one of which was excluded, being a rehabilitation protocol without results on patients.

Every full text was examined, and characteristics of the study, study sample, type of rehabilitation and treatment, outcome measures and results were extracted from the full text and summarized in Table 1.



**Table 1.**Characteristics of examined studies.

*J. Clin. Med.* **2020**,*9*, 3115






*J. Clin. Med.* **2020**, *9*, 3115



K-GDS = Korean version of the geriatric depression scale; EQ-5D = Euro quality-of-life questionnaire 5-dimensional classification; K-MBI = Korean modified Barthel index; K-IADL = the Korean instrumental activity of daily living.

Upon the seven full texts eligible for this review, three examined the impact of conventional rehabilitation and nutritional supplementation, based on food richness of proteins and aminoacids, on patients affected by sarcopenia following FNF [16,19,20] Three papers evaluated the effects of rehabilitation protocols only, especially comparing new methods to conventional rehabilitation and evaluating the impact of sarcopenia on rehabilitation progress [21–23]. A study explored the intervention with erythropoietin (EPO) in sarcopenic patients with femoral intertrochanteric fractures and its potential effects on postoperative rehabilitation. [24]

#### *3.2. Sarcopenia Diagnosis*

Various definitions of sarcopenia have been developed by different international consensus panels, (the Asian Working Group on Sarcopenia (AWGS), the European Working Group on Sarcopenia in Older People (EWGSOP) and the Foundation of the National Institute of Health, International Working Group on Sarcopenia) each defining cut-off values from mobility limitation measures (appendicular skeletal mass index, grip strength and physical performance). In our review, the authors specifically used the diagnostic criteria included in the AWGS [21–25] and EWGSOP [1,16,19,20].

The EWGSOP defines sarcopenia when ASM is less than 20 kg for men and 15 kg for women, ASM/height<sup>2</sup> is less than 7.0 kg/m<sup>2</sup> for men and 5.0 kg/m<sup>2</sup> for women (muscle quantity), grip strength is less than 27 kg for men and 16 kg for women, chair stand > 15 s for five rises (muscle strength), gait speed is no more than 0.8 m/s, short Ppysical performance battery (SPPB) is less than 8 points, timed up and go (TUG) test is less than 20 s and 400 m walk test is completed in more than 6 min or not completed at all (physical performance) [1].

AWGS criteria include decreased handgrip strength (males < 28 kg, females < 18 kg), physical performance evaluated with gait speed ≤ 0.8 m/s or 5-time chair stand test: ≥12 s or short physical performance battery: ≤9, and loss of muscle mass, indexed by appendicular skeletal muscle mass (ASM) divided by height squared evaluated through dual-energy X-ray absorptiometry (M: <7.0 kg/m2, F: <5.4 kg/m<sup>2</sup> ) or bioelectrical impedance analysis (M: <7.0 kg/m<sup>2</sup> , F: <5.7 kg/m<sup>2</sup> ) [25].

#### *3.3. New Rehabilitation Protocols*

In Study 1 (Table 1), the functional outcomes of a new integrated rehabilitation management (FIRM) were assessed in sarcopenic and nonsarcopenic inpatients [21]. Sixty-eight patients (32 Sarcopenic and 36 nonsarcopenic) who had undergone surgery for fragility FNF were included.

FIRM included intensive physical and occupational therapy, fall prevention education with discharge planning and referral to community-based care. After surgery, the patients stayed in hospital with 10 days of physical therapy with two sessions per day and four days of occupational therapy. Physical therapy consisted of weight bearing exercises, strengthening exercises, gait training and aerobic exercise, and functional training progressed gradually based on the individual's functional level. Occupational therapy aimed to train the patients in ADL (transfer, sit to stand, bed mobility, dressing, self-care retraining and using adaptive equipment).

The outcome measures used in the eligible studies were walking ability through two scales: the KOVAL walking ability scale [26] and the functional ambulatory category (FAC) [27]; general mobility; balance and fall risk; cognitive functioning; quality of life; mood; ADL; frailty and handgrip strength of the patients; modified Rivermead mobility index [28]; Berg balance scale [29]; MMSE [30]; Korean version of the geriatric depression scale [31]; the Euro quality-of-life questionnaire 5-dimensional classification [32]; the Korean modified Barthel index [33]; the Korean instrumental ADL [34] and the Korean version of the fatigue, resistance, ambulation, illnesses and loss of weight (FRAIL) scale [35]) at admission to the in-hospital rehabilitation unit and at discharge.

KOVAL and FAC were significantly improved in both sarcopenic and nonsarcopenic patients. Prefacture ambulatory functioning, rather than the presence of sarcopenia, was significantly correlated with short-term recovery of ambulatory functioning. Mobility, balance, cognitive functioning and quality of life improved in both groups, demonstrating the clinical effectiveness of FIRM in sarcopenic

patients. In contrast, K-IADL (*p* = 0.029) and K-FRAIL (*p* = 0.023) scores were significantly improved in only the nonsarcopenia group after rehabilitation.

Limitations of this study were the short time after which the outcomes were evaluated (after two weeks of interventions) and the exclusion of several patients before the start of the treatment. The use of the sarcopenia classification itself may have affected the group allocation. Even though the results of Study 1 suggest that FIRM was effective for short-term functional recovery in older patients with or without sarcopenia who have suffered fragility hip fracture, further research comparing FIRM with conventional therapy is needed.

Study 2 (Table 1) [22] evaluated the FIRM program in a prospective observational investigation of 80 patients (35 Sarcopenic and 45 nonsarcopenic) older than 65 after FNF surgery. The author, unlike the previous study, ruled out gait speed from the diagnostic criteria for sarcopenia in the sample evaluated because this result could not be estimated before the fracture or surgery. The FIRM program was administered during two weeks of hospital stay after surgery. All functional outcomes (KOVAL, FAC, EQ-5D, K-IADL, and K-FRAIL) were assessed on admission for rehabilitation, at discharge, and at the three and six months follow-up visits after surgery (or with a telephone interview). In the considered sample, patients with sarcopenia had impairment in cognitive function in a significantly superior percentage than the nonsarcopenic group. Both groups had improvement in the primary outcome (KOVAL) and functional outcome (FAC score) after discharge. Other evaluations, excluded HGS, significantly improved in both groups with no significant difference. Even though sarcopenia was not a predictor of poorer results in ambulatory independence, at six months from surgery, the type of operation and high HGS (handgrip strength) were significantly correlated.

Study 2 [22] demonstrated that ambulation and functional outcomes were improved in patients with or without sarcopenia suffering from fragility after FNF surgery, due to a complete multidisciplinary rehabilitation. Limitations were caused by the assessment of sarcopenia in patients soon after the surgery, namely the time of follow-up that in fragile patients may have been longer, and the lack of a control group following conventional rehabilitation.

Study 3 [23] compared the efficacy of an antigravity treadmill (AGT) combined with conventional physical therapy, and physical therapy alone, in a double-blinded (to outcome) study. Selected patients were 65–90 years old, who had undergone surgery for FNF associated with sarcopenia, according to the AWGS recommendation [25]. Thirty-eight patients included in the primary analysis were treated. One group (*n* = 19) had only standardized rehabilitation treatment for 30 min per day for 10 days, the other (*n* = 19) received standardized treatment plus AGT for 20 min per day. Standardized therapy consisted in passive hip and knee mobilization, strengthening of the hip abductor and extensor muscles, transfer, and gait training on the floor and stairs.

The outcomes evaluated were the same as Studies 1 and 2 [21,22], except for the absence of the I-ADL measurement. The experimental group experienced higher and longer therapeutic effects, with improvement in all outcomes. However, in both groups, KOVAL and FAC scores were slightly improved and then decreased from 3 three to 6 months. This study provided evidence not only that AGT with CR is more effective than only CR for sarcopenic patients, but also that there is a strong association between muscle mass and bone mass, supporting the theory that muscle forces mediate mechanical loading effects on bones [36]. Limitations of Study 3 were the high amount of drop outs after hospital discharge, it was carried out in only one center, and the number of the sample was not sufficient to significantly represent subgroups with different cognitive function, hip fracture and hip operation type.

#### *3.4. Nutritional Supplements and Physical Therapy*

Study 4 (Table 1) [16] was a randomized controlled study evaluating the effects of combined therapy with bisphosphonate, protein-rich nutritional supplementation and conventional rehabilitation in 79 sarcopenic patients after FNF [16]. Measured parameters were body composition, hand grip strength (HGS) and health-related quality of life (HRQoL). Patients were randomized into three

treatment groups. All patients received calcium 1 g and vitamin D 800 I.E. divided into two daily doses for 12 months. The nutritional supplementation group (protein + energy = N group, *n* = 26) received a 200 mL package twice daily, each containing 20 g of protein and 300 kcal. This supplement was given for the first six months after FNF, combined with 35 mg risedronate once weekly for 12 months. The second group (B, *n* = 28) received risedronate alone, 35 mg once weekly for 12 months. The controls (C, *n* = 25) received only calcium and vitamin D for 12 months. Treatment began as soon as the patients were medically stable after surgery, able to take orally administered medications and able to sit upright for one hour after intaking bisphosphonates.

Energy supplementation combined with bisphosphonate, vitamin D and calcium had no positive effect on hand-grip strength, HRQoL, or lean mass, when compared to administration of bisphosphonate along with vitamin D and calcium supplementation, or just vitamin D and calcium supplementation, after FNF. Protein and energy supplementation combined with conventional rehabilitation was not able to preserve lean mass after a hip fracture better than vitamin D and calcium alone or combined with bisphosphonates. There were no intergroup differences concerning effects on HGS or HRQoL, but intragroup improvement in HGS, and a positive effect on HRQoL, were seen in the nutritional supplementation group. A limitation of this study was the small sample size.

In Study 5 (Table 1) [19], 32 patients (23 Sarcopenic, nine nonsarcopenic) aged more than 65 years were enrolled three months after osteoporotic FNF and treated with total hip replacement. The authors evaluated the impact of a two months rehabilitative protocol, combined with dietetic counseling with or without essential aminoacid supplementation, on functioning. Patients were divided into two groups. Patients in group A (*n* = 16, 11 Sarcopenic, five nonsarcopenic) were treated for two months with essential aminoacid supplementation sachets of 4 g per day. Furthemore, patients performed a concomitant specific physical exercise rehabilitative program consisting of five sessions of 40 min each per week for two weeks with the supervision of an experienced physiotherapist, and received dietetic counseling. The physical activity included walking training, resistance and stretching exercises and balance exercises. After these two two weeks, all participants performed a home-based exercise protocol up to the end of the study period, two months from intervention. Patients in group B (*n* = 16, 12 Sarcopenic and four nonsarcopenic) performed the same physical exercise rehabilitative program as group A and received concomitant dietetic counseling alone, without essential amino acid supplementation.

Outcome measures were the hand grip strength test (HGS), physical performance, using the timed up and go test (TUG) [37], level of assistance measured by the Iowa level of assistance scale (ILOA) [38], nutritional assessment, with evaluation of daily caloric intake and daily protein intake, and the health-related quality of life (HRQoL) evaluation. All outcome measures were assessed at baseline (T0) and after two months of treatment (T1). Patients in both groups were divided into sarcopenic and nonsarcopenic patients. All patients in both groups showed statistically significant differences in all primary outcome measures (HGS, TUG, ILOA) at the T1 evaluation (*p* < 0.017). Sarcopenic patients in group A showed statistically significant differences in all primary outcomes (HGS, TUG, ILOA) at T1 (*p* < 0.017), whereas sarcopenic patients in group B showed a significant reduction of ILOA at the end of treatment. On the other hand, in nonsarcopenic patients, they found no differences at T1 in the TUG test and level of assistance test. In both groups, there were no differences at T1 in all other outcome measurements. Furthermore, there were no differences between groups in all outcome measuresments both at baseline and after two months of treatment.

Even though it was performed on a small sample size, data emerging from this study showed a good impact of this combined intervention on function and disability in hip fracture patients after two months of treatment. Essential amino acid supplementation induced considerable improvements in the sarcopenic subpopulation of the study.

Study 6 (Table 1) [20] was a multicentric randomized trial evaluating a nutritional supplement, enriched with β-hydroxy-β-methylbutyrate (HMB), calcium (Ca) and 25-hydroxy-vitamin D (25(OH)D) during rehabilitation therapy to improve muscle mass and, thereby, functional recovery. It included 107 sarcopenic patients aged more than 65 years old with FNF. There were 15 drop-outs during the study. This was the first study to evaluate the effects of HMB in sarcopenic patients with hip fractures. Patients in the intervention group (IG, *n* = 49) received a standard diet plus oral nutritional supplementation enriched with 0.7 g/100 mL of HMB, 227 IU/100 mL of 25(OH)D and 227 mg/100 mL of Ca, while those in the control group (CG, *n* = 43) received a standard diet only. Physical therapy was based on moving patients early, using technical aids, and rehabilitation of activities of daily living including exercises to strengthen the lower limbs, balance exercises and walking retraining in individual or group 50 minute sessions, once a day five days a week. Outcomes measured were gait speed, hand grip strength, appendicular lean mass (aLM, kg/height<sup>2</sup> ), nutritional assessment carried out by the Mini Nutritional Assessment-Short Form (MNA-SF) [39] and patients' functional situation using the Barthel index (BI) [40] and the functional ambulation categories (FAC) score [27].

The outcome variable was the difference between aLM upon discharge and aLM upon admission (∆-aLM). BMI and aLM were stable in intervention group (IG) patients, whilst these parameters decreased in the control group (CG). The concentration of proteins (*p* = 0.007) and vitamin D (*p*.001) increased more in the IG than the CG. A positive effect of oral nutritional supplementation was reported on recovery of ADL. The recovery of ADL was more common in the intervention group (68%) than in the control group (59%) (*p* = 0.261).

This study had a number of limitations. Patients received rehabilitation five days a week. It would be interesting to see whether participation in a program of resistance exercises during the patients' stay at a rehabilitation center improved the functional results reported. The authors could not do any follow-up of patients after discharge to assess whether the benefits obtained were maintained. Furthermore, diagnostic criteria for sarcopenia proposed by the EWGSOP were difficult to apply in patients with hip fractures admitted to rehabilitation units, because most of the patients were unable to walk when they arrived. Despite these limitations, this research had some important strengths. Due to the characteristics of the patients included, this study could be representative of the geriatric population admitted to rehabilitation centers.

#### *3.5. Other Treatments*

Study 7 (Table 1) [24] assessed the effects of recombinant human erythropoietin (EPO), already used in in sarcopenic patients for perioperative recovery, in patients with femoral intertrochanteric fracture and sarcopenia, to investigate its potential benefits on postoperative rehabilitation. EPO, through the activation of the signaling cascades in hematopoietic cells, may stimulate proliferation and differentiation of skeletal muscle myoblasts, making the skeletal muscle a potential target [41,42].

The effects of EPO were analyzed in 141 sarcopenic patients older than 60 years with intertrochanteric femoral fracture, randomly divided in intervention and control groups and examined by sex. The intervention group (*n* = 83) received recombinant human erythropoietin via intravenous injection once per day for 10 days after surgery. All patients, including the control group (*n* = 58) received adequate nutrition and exercise for recovery. The outcomes evaluated were: handgrip strength, appendicular skeletal muscle (ASM) index and postoperative hospitalization and infection. The intervention group, especially in female patients, had significant improvement in handgrip strength during the first week after the surgery. The improvement was consistent in the following three weeks. Even the ASM index was improved, with a more important improvement, but not significant, in the intervention group. The rate of post-operative infection and length of hospitalization were significantly decreased in patients who received EPO intervention.

#### **4. Discussion**

In this review, we considered seven studies of older adults (>60 years) in which both rehabilitation and nutrition, alone or combined, were used to improve recovery after hip fracture surgery in terms of walking independence, muscle strength, mobility, live activity and fragility. The studies included participants with different degrees of general, cognitive and mobility functions, who had experienced different types of fracture and undergone various surgery methods. The rehabilitation and supplementation strategies, as well as study designs (duration and setting) were different.

The main finding was that sarcopenia, being a multifactor disease, needs a treatment that cannot rely on a single drug. The treatment should be a combination of methods including nutritional intervention, intervention of functional exercise and medications [24]. Physical inactivity was negatively linked to losses of muscle mass and strength, suggesting that increasing levels of physical activity should have protective effects. Also, muscle strength is a critical component of walking, and its decrease in the elderly contributed to a high prevalence of falls [6,43]. Furthermore, early ambulation after hip fracture had beneficial effects on functioning, readmission rate and multidisciplinary rehabilitation reducing the risk of poor outcomes, such as death and admission to nursing homes following FNF [44].

To strengthen muscle and physical function, progressive resistance exercise training is a commonly used tool [21–23]. Ambulatory independence is a crucial outcome to examine in patients after hip-surgery, and it must be evaluated before and after the surgery intervention and rehabilitation protocol. In Study 1 [21], it was found that ambulatory independence is more associated with individual ambulatory function before the fracture than in the presence of sarcopenia. However, Study 2 [22] considered poor ambulatory independence as predictive factor for worse results in the evaluated outcome.

Progressive resistance training, associated with occupational therapy, in the above-mentioned studies, resulted in important improvements in walking ability, strength and general mobility, especially in the short-term rehabilitation of sarcopenic patients. Occupational therapy may also have an important role in cognitive function. Cognitive function is a crucial factor, affecting the rehabilitation outcomes after FNF in patients. When occupational therapy was not involved, there was no significant difference in outcome measurements between the two groups at all follow-ups in K-MMSE [21,22].

Type and intensity of exercise is an important variable that significantly influences functional outcomes in FNF patients. Study 3 [23], compared the effects of antigravity treadmill rehabilitation with conventional rehabilitation and conventional rehabilitation alone, and which did not include progressive resistance training and was uncertain in terms of compliance, found an important and significant improvement in the ability to walk, ambulatory function, general mobility, balance and quality of life in the experimental group. The antigravity treadmill, in fact, allowed a task-specific repetitive approach, facilitating the practice of numerous complex gait cycles, which were not possible in the control group.

In the literature, less is reported about the role of diet in older age, although there is evidence that improvements in diet among older adults at risk of developing sarcopenia may have the potential both to prevent, or delay, age-related losses of muscle mass and function, as well as being potential management strategies for sarcopenic patients. However, existing evidence from nutrient supplementation studies is mixed [2,6].

In our review, the effects of provision of additional amino acids, protein, bisphosphonates, calcium, Vitamin D and HMB, in combination with a standardized diet and exercise training, were reported. The supplements differed in type, dose, frequency and delivery among the patients, as did the results and improvement in patients. The sample was somewhat evenlydistributed in terms of age, sex and type of fracture. All three studies (Studies 4, 5 and 6) showed that supplemental nutrition improved functional results in patients with sarcopenic FNF. However, some findings must be discussed. Study 4 [16] did not confirm any hypothesis because the improvements were not significant between the different groups. However, in the nutritional supplementation group, analysis did show a positive effect on quality of life and handgrip strength. In the other two studies, significant improvement was seen in ADLs, in particular, and in HGS and walking ability in the intervention groups [19,20]. Moreover, Study 5 [19] found that sarcopenic patients with amino acid intake had important improvements in ADLs, compared to other groups. The same difference did not occur in the nonsarcopenic patients. The improvement disappeared after two months when the intake was

suspended. This may prove the importance of amino-acid supplementation, especially in sarcopenic patients after hip surgery, beinmg maintained for a longer period in older adults.

As for medical therapy, no drugs are specifically designed for the treatment of sarcopenia. Testosterone, growth hormone and beta-adrenergic receptor agonists are commonly used to improve sarcopenia [45], but more research is needed because they do not always improve muscle function [46].

Study 7 [24] tried to include EPO as a drug to treat sarcopenia when used as a perioperative red blood cell mobilization drug in patients with FNF. The authors found that EPO improved the muscle strength of female patients with sarcopenia during the perioperative period, increased muscle mass of both women and men to a certain degree and significantly reduced the incidence of complications during the preoperative period. EPO may work as a new treatment option for patients with FNF in short-term postoperative rehabilitation.

#### **5. Conclusions**

Physical activity, in its various forms, and dietary supplementation, are the basic tools of prevention and rehabilitation of sarcopenia in elderly patients after hip surgery. Exercise training increases muscle mass in the elderly population with varying fragility and nutritional status, helping outpatient recovery, which is the primary outcome in these patients. The most effective physical therapy seems to be exercise of progressive resistance. However, occupational therapy should be included in sarcopenic patients for its importance in cognitive rehabilitation, especially in older adults, to help their return to normal daily activities. Nutritional support, combined with task-specific repetitive exercises, is supported by accumulating evidence for improving sarcopenia and preventing disability. Protein-rich dietary supplementation should primarily include amino acids for a long period in elderly patients. Treatment should include medical therapy, such as erythropoietin and bisphosphonates, which are increasingly important resources, even though they need further research for their validation.

**Author Contributions:** Conceptualization, G.R.A.M. and M.A.; methodology, M.A.; software, A.V.; validation, G.T., V.P. and M.V.; formal analysis, S.M.; investigation, G.R.A.M.; resources, M.A.; data curation, A.V.; writing—original draft preparation, G.R.A.M.; writing—review and editing, M.A.; visualization, A.V.; supervision, G.T.; project administration, M.V.; funding acquisition, V.P. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Review*

### **Resistance Exercise, Electrical Muscle Stimulation, and Whole-Body Vibration in Older Adults: Systematic Review and Meta-Analysis of Randomized Controlled Trials**

### **Nejc Šarabon 1,2,3,\* , Žiga Kozinc 1,4, Stefan Löfler 5,6 and Christian Hofer <sup>7</sup>**


Received: 31 July 2020; Accepted: 7 September 2020; Published: 8 September 2020

**Abstract:** It has been shown that resistance exercise (RT) is one of the most effective approaches to counteract the physical and functional changes associated with aging. This systematic review with meta-analysis compared the effects of RT, whole-body vibration (WBV), and electrical muscle stimulation (EMS) on muscle strength, body composition, and functional performance in older adults. A thorough literature review was conducted, and the analyses were limited to randomized controlled trials. In total, 63 studies were included in the meta-analysis (48 RT, 11 WBV, and 4 EMS). The results showed that RT and WBV are comparably effective for improving muscle strength, while the effects of EMS remains debated. RT interventions also improved some outcome measures related to functional performance, as well as the cross-sectional area of the quadriceps. Muscle mass was not significantly affected by RT. A limitation of the review is the smaller number of WBV and particularly EMS studies. For this reason, the effects of WBV and EMS could not be comprehensively compared to the effect of RT for all outcome measures. For the moment, RT or combinations of RT and WBV or EMS, is probably the most reliable way to improve muscle strength and functional performance, while the best approach to increase muscle mass in older adults remains open to further studies.

**Keywords:** sarcopenia; falls; elderly; resistance exercise; vibration; electrical stimulation

#### **1. Introduction**

With rising life expectancy and the increasing proportion of older adults in the population [1,2], effective interventions that promote lifelong well-being and health are more needed than ever before. There is no doubt that performing physical exercise is one of the most effective ways for older adults to maintain functional independence, maintain physical abilities, and reduce the risk of various diseases and injuries [3–7]. One of the most notable changes associated with aging is sarcopenia, which is characterized by a loss of muscle mass and other subsequent changes, such as reduced muscle strength and impaired functional ability [8]. Together with nutritional interventions, resistance exercise training

(RT) seems to be the most effective approach to prevent and treat sarcopenia [9–11]. Falls are also one of the major problems in the older adult population [12] and are thus given considerable attention in terms of prevention. It has been shown that the best way to prevent falls is by performing RT alone or in combination with other exercise types or other interventions [13,14]. Despite extensive research regarding the effects of resistance exercise on sarcopenia, fall risk, and general health of older adults, the recommendations for prescribing exercises in this population are still relatively vague and generic [3,11,15]. In contrast, previous studies have investigated several factors that are worth considering in order to maximize the effects of RT for older adults, such as intensity [16], speed of movement [17], and supervision of the training sessions [18]. Certain types of RT, such as speed-power training [19], are also increasingly being investigated as potentially superior to traditional resistance exercise.

Recent literature reviews have found numerous barriers, such as decreased physical ability, walking disability, lack of companionship, and lack of motivation, that are decreasing the participation of older adults in exercise programs [20,21]. For this reason, different methods to combat sarcopenia, prevent falls, and increase well-being in older adults should be considered as an alternative to RT. Recently, whole-body vibration (WBV) has been shown to improve postural balance [22] and muscle strength [23] and to reduce the likelihood of falls in older adults [24]. WBV is therefore a possible alternative to RT; however, direct comparisons between the effects of RT and WBV are lacking. Roelants et al., reported similar improvements in knee extension strength, jumping performance, and speed of movement after 12 and 24 weeks of RT and WBV interventions in older women [25]. Similarly, Bogaerts et al., showed comparable effects of WBV and RT on muscle mass and muscle strength in older men [26]. Another promising alternative to RT is electrical muscle stimulation (EMS) [27–31]. EMS has been shown to improve functional performance of aging muscles [27,31] and to counteract muscle decline in old age [30]. Moreover, EMS has been appreciated as a convenient intervention for older adults with lower physical abilities or low motivation to exercise [32].

Although many positive effects of RT, WBV, and EMS in older adults have been consistently demonstrated, it is not entirely clear which interventions should be prioritized for the best health benefits. Moreover, studies often follow only a limited set of outcome measures, making comparisons between interventions difficult. Therefore, the objective of this work was to provide a comprehensive systematic review with meta-analysis of high-quality studies that assessed the effects of RT, WBV, or ES in older adults. To obtain a broad overview of these effects, we included studies that assessed various outcome measures, including muscle strength, body composition, and muscle morphology, and the outcomes of functional performance tests. In addition, the aim of this review was to examine the effects of several independent variables, pertaining to the intervention programs, such as (but not limited to) intervention duration, weekly frequency, volume, intensity, supervision, and compliance. We hypothesized that RT, WBV, and EMS will have similar effects on body composition, muscle strength, and functional performance.

#### **2. Materials and Methods**

#### *2.1. Inclusion Criteria*

Study inclusion criteria were structured according to PICOS tool [33]:


### *2.2. Search Strategy*

Multiple databases of scientific literature (PubMed, Cochrane Central Register of Controlled Trials, PEDro, and ScienceDirect) were searched in May 2020 without regard to the date of publication. For the databases that enable using Boolean search operators, we used the following combination of search key words: (sarcopenia OR muscle atrophy OR muscle wasting) and (training OR exercise OR vibration OR electrical stimulation OR electrostimulation OR magnetic stimulation OR vibration training OR physical therapy) and (strength OR power OR muscle mass OR muscle diameter) and (elderly OR older OR older adults OR ageing OR age-related). Otherwise, we used several reduced combinations of key words, including, but not limited to resistance exercise older adults, vibration training elderly, electrical stimulation elderly and older adults sarcopenia intervention. Additionally, reference lists of several review articles describing interventions for older adults were carefully scrutinized. Finally, we carefully reviewed reference lists of all articles that were already retrieved through the database search and were published within the last 4 years. The database search was performed independently by two authors (N.Š. and Ž.K.). Two reviewers (N.Š. and S.L.) also screened the titles and the abstracts independently. Potentially relevant articles were screened in full text, followed by additional screening for their eligibility by the additional reviewers.

#### *2.3. Data Extraction*

The data extraction was carried out independently by two authors (Ž.K. and C.H.) and disagreements were resolved through consultation with other authors. The extracted data included: (a) baseline and post-intervention means and standard deviations for all eligible outcome measures for interventional and control groups; (b) baseline demographics of participants (gender, age, body height, body mass, body mass index); (c) intervention characteristics (target body area (upper, lower or whole-body), duration of the intervention, number of sessions per week, volume (number of exercises, sets, and repetitions), breaks between exercises and sets, supervision, and progression of exercise difficulty). For studies examining RT, we also extracted the type of load used (bodyweight, machine, elastics, weights, etc.) and intensity as a percentage of 1-maximum repetition (1RM) or subjective measures, such as the Borg scale. For EMS studies, we further extracted the stimulation frequency and amplitude, the stimulated body parts, pulse shapes, and breaks between repetitions or sets. For WBV studies, we additionally extracted the amplitude and the frequency that was used during training. Data were carefully entered into Microsoft Excel 2016 (Microsoft, Redmond, WA, USA). If the data were presented in a graphical rather than tabular form, we used Adobe Illustrator Software (version CS5, Adobe Inc., San Jose, CA, USA) to accurately determine the means and standard deviations. In case of missing data, the corresponding author of the respective articles was contacted by e-mail. If no response was received after 21 days, the author was contacted again. If the author did not reply to the second inquiry, the data was considered irretrievable.

#### *2.4. Assessment of Study Quality*

Two authors (Ž.K. and N.Š.) evaluated the quality of the studies using the PEDro tool [34], which assesses study quality based on a ten-level scale. Potential disagreements between ratings were resolved by consulting the other authors. Studies scoring from 9–10 were considered as "excellent," 6–8 as "good," 4–5 as "fair," and less than 4 as "poor" quality. The PEDro scale was chosen because it was developed specifically to assess the quality of randomized controlled trial studies evaluating physical therapist interventions [34].

#### *2.5. Data Analysis and Synthesis*

The main data analyses were carried out in Review Manager (Version 5.3, Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2014, London, UK). Before the results were entered into the meta-analytical model, the pre-post differences and pooled standard deviations were calculated according to the following formula SD = √ [(SDpre <sup>2</sup> + SDpost 2 ) − (2 × r × SDpre × SDpost). The correction value (r), which represents the pre-test–post-test correlation of outcome measures, was conservatively set at 0.75. It should be noted that a change in the correction value in the range between 0.5 and 0.9 had little effect on the pooled SD and would not change the outcomes of the meta-analyses. For the meta-analyses, the inverse variance method for continuous outcomes with a random-effects model was used. The pooled effect sizes were expressed as mean difference (MD) where possible, which allows the effect size to be expressed in units of measurement. Where this was not possible due to the heterogeneity of the outcome variables (e.g., muscle strength reported in kg, N, Nm, N/kg, and Nm/kg), the effect sizes were expressed as standardized mean difference (SMD). For MD and SMD, the respective 95% confidence intervals were also calculated and reported.

Basic analysis compared the effects of the RT, EMS, and WBV interventions. Further subgroup analyses were conducted where possible (depending on the number of studies reporting a given outcome) based on several independent variables, related to the characteristics of the interventions (e.g., weekly number of sessions). Some outcomes did not appear in EMS and WBV studies and were thereby only analyzed in view of RT studies. Statistical heterogeneity among studies was determined by calculating the I2 statistics. According to Cochrane guidelines, the I2 statistics of 0% to 40% might not be important, 30% to 60% may represent moderate heterogeneity, 50% to 90% may represent substantial heterogeneity, and 75% to 100% indicates considerable heterogeneity [35]. The threshold for statistical significance was set at *p* ≤ 0.05 for the main effect size and the subgroup difference tests.

Sensitivity analysis was performed when deemed necessary i.e., by examining the effect of exclusion of certain studies from the analyses (e.g., studies that could have included subsets of previous studies, studies with very low compliance, studies that did not report intensity, studies with and without elderly with sarcopenia, etc.). The sensitivity analyses showed no or very little effect on the main results (SMD changes = 0.01–0.10), except where noted and reported in the results.

#### **3. Results**

#### *3.1. Summary of Search Results*

The results of the search steps are summarized in Figure 1. The search resulted in 64 studies in total, 48 of which included RT interventions (55 intervention groups in total), 12 included WBV interventions (14 intervention groups in total) and 4 included EMS interventions (4 intervention groups in total). A table encompassing all the details regarding the participants, interventions and outcomes of individual studies is included in Supplementary data 1.

**Figure 1.** Summary of search results. RT—resistance training; WBV—whole-body vibration; EMS—electrical muscle stimulation.

#### *3.2. Study Quality Assessment*

The PEDro scale scores indicated overall fair to good quality of the RT studies (mean = 5.25 ± 1.26; median = 5.0; range = 2–8) and WBV studies (mean = 5.41 ± 1.24; median = 5.5; range = 4–7). Studies exploring EMS were all rated as good (mean = 6.52 ± 1.03; median = 6.0; range = 6–8). The most common items that almost all studies failed to satisfy were blinding of the subjects, therapists and assessors.

#### *3.3. Participant Data and Intervention Characteristics*

In total, there were 2017 participants (1158 in intervention groups and 1026 in control groups) in the RT studies, 606 in WBV studies (325 in intervention groups and 284 in control groups), and 192 in the EMS studies (99 in intervention groups and 93 in control groups). Across all studies, the pooled participant age was 73.5 ± 4.8 years (range of means: 65–92 years), the pooled participant body mass was 65.8 ± 10.33 kg (range of means: 40.5–101.8 kg), and the pooled body mass index was 26.39 ± 3.77 kg/m<sup>2</sup> (range of means: 18.8–36.7 kg/m<sup>2</sup> ). In total, 36 included participants of both genders, 24 studies included only females, and 4 studies included only males. In 16 RT studies, sarcopenia was listed as an inclusion criterion. In 47 studies, the interventions were supervised, while the interventions in the remaining studies were not supervised (*n* = 9) or the information regarding the supervision was missing (*n* = 7). The most typical duration of the interventions was 12 weeks (*n* = 28), while 12 interventions were shorter (4 interventions lasted 5–6 weeks, and 8 interventions lasted 8–11 weeks) and 23 interventions were longer (12 interventions lasted 13–24 weeks, and 11 interventions lasted 25 weeks or more). Most interventions included either 2 (*n* = 23) or 3 (*n* = 32) sessions per week, while 5

interventions were performed once per week and 3 interventions were performed 4–5 times per week. Only 4 WBV and 19 RT studies reported adherence to the intervention program, with mean values of 90 ± 3% and 84 ± 9%, respectively.

Across the RT studies, 14 intervention programs used machines, 6 used free weights, 5 used elastic resistance, 4 implemented bodyweight exercises, 1 used weighted tai-chi exercises, and 1 used isoinertial exercises on a flywheel device. The remaining 17 studies used mixed approaches (5 combined bodyweight and elastic exercise, 2 combined free weights and bodyweight exercises, 3 combined free weights and machines, and 7 used more three or four types of load). RT interventions included either full body workout (*n* = 32) or focused on the lower limb muscles (*n* = 16), while no interventions focused only on the trunk or the upper limbs. Most often (*n* = 29), the intervention included a combination of single-joint and multi-joint exercises; however, some interventions included predominantly single-joint (*n* = 12) or multi-joint (*n* = 7) exercises. The volume of exercise varied substantially between studies, with the number of exercises ranging from 1 to 12 (mean: 5.9 ± 2.9), the number of sets ranging from 1 to 5 (mean: 2.7 ± 0.8), and number of repetitions within sets ranging from 7 to 25 (mean: 11.0 ± 3.5). Intensity was set as percentage of 1-repetition-maximum in 27 studies (mean: 66.2 ± 15.3%; range: 20–80%) or using the 6–20 Borg scale for assessment of the rate of perceived exertion in 10 studies (all studies used 13 as the target value). One study determined the intensity as percentage of maximal heart rate (set between 60 and 80%). The remaining 12 studies did not report the intensity of the exercise. Breaks between sets were reported in 11 studies and ranged from 30 s to 150 s (mean: 100 ± 45 s). Breaks between exercises were only reported in 5 studies (range: 90–180 s).

In WBV studies, the number of exercises ranged from 1 to 9 (mean: 3.8 ± 3.1) and the number of sets ranged from 1 to 10 (mean: 3.5 ± 2.7). With the exception of 1 study, which used highly varying vibration frequency (27–114 Hz), the frequencies used ranged from 20 to 60 Hz (mean: 35.7 ± 10.1 Hz). The amplitude of the vibration ranged from 2 to 6 mm (mean: 3.8 ± 1.4 mm). Breaks between sets ranged from 30 to 180 s (mean: 75 ± 53.8 s).

Finally, 3 EMS studies targeted full body (all used stimulation frequency of 85 Hz, impulse width at 350 µs, moderate intensity (subjectively determined) and lasted 20 min per session), while 1 study stimulated only the lower limbs (frequency: 100 Hz; amplitude: 40–120 mA; impulse width: 400 µs).

#### *3.4. E*ff*ects of RT and WBV on Muscle Strength*

Knee extension strength was by far the most common outcome across studies and was reported in 2 EMS studies with 2 intervention groups [36,37], 6 WBW studies with 8 intervention groups [25,26,38–42], and 26 RT studies with 29 intervention groups [25,43–67]. In total, 5 studies measured isokinetic strength (1 study at 30◦ /s, 3 studies at 60◦ /s and 1 study sat 90◦ /s), and the rest measured isometric strength. Figure 2 displays the main analysis, comparing the effect of WBV, RT, and EMS on knee strength. Due to substantial discrepancy between the studies in terms of units of reporting, only the SMD could be computed.

There was a statistically significant increase in knee extension strength in the intervention groups across all studies compared to control groups (SMD = 1.12 (0.86–1.37); *p* < 0.001; I<sup>2</sup> = 83%). Both WBV interventions (SMD = 0.97 (0.34–1.59); *p* = 0.00; I<sup>2</sup> = 90%) and RT interventions (SMD = 1.24 (0.96–1.52); *<sup>p</sup>* <sup>&</sup>lt; 0.001; I<sup>2</sup> <sup>=</sup>79%) improved knee extension strength, while EMS did not (SMD <sup>=</sup> <sup>−</sup>0.08 (−1.08–0.91); *p* = 0.88; I<sup>2</sup> = 81%). RT appeared superior to WBV; however, the difference between intervention types was not statistically significant (*p* = 0.32). For WBV, the subgroup analysis was performed for intervention duration and indicated that interventions longer than 24 weeks have a higher effect (SMD = 1.61 (0.35–2.87) than interventions lasting up to 12 weeks (SMD = 0.55 (0.21–0.88) or interventions lasting 13–24 weeks (SMD = 0.55 (−0.29–1.40)), although the subgroup test showed that this difference was not statistically significant (*p* = 0.28). Within the RT studies, most interventions lasted 12 weeks (17/26 studies). Subgroup analyses showed no effect of intervention duration on knee strength increases (SMD = 0.94–1.26 across subgroups). The effect of RT was the highest in studies with participants aged > 80 years (SMD = 1.76 (1.01–2.52), lower in the < 70-year-old subgroup (SMD =

1.17 (0.73–1.61) and the lowest in the 70–80-year-old subgroup (SMD = 0.95 (0.65–1.25)) (*p* = 0.14 for subgroup differences). The effect was comparable in studies using predominantly single-joint (SMD = 1.38 (0.70–2.07), predominantly multi-joint (SMD = 1.12 (0.33–1.90)), or a combination of singleand multi-joint exercises (SMD = 1.27 (0.91–1.62)) (*p* = 0.88 for subgroup differences). No differences between studies were found (*p* = 0.68) based on the type of resistance, though there was a trend for higher effect of interventions based on machine training (SMD = 1.36 (0.97–1.75)) and free weights (SMD = 1.33 (0.37–2.29)) compared to elastic resistance (SMD = 0.91 (0.20–1.63)) and approaches that combined multiple types of resistance (SMD = 0.98 (0.49–1.47)). Finally, studies were grouped according to number of sessions per week and no differences were found between interventions performed ≤2 times per week (SMD = 1.30 (0.92–1.68)) and ≥3 times per week (SMD = 1.15 (0.75–1.55)) (*p* = 0.59 for subgroup differences).


Sensitivity analysis was performed to examine the effect of certain concerns regarding the studies. Since it was not entirely clear if Bogaerts et al. (2007 and 2009, see Figure 2, top section) reported the data for entirely different sample in the two studies, we excluded the study with smaller sample size. The pooled effect of WBV was decreased from 0.97 to 0.88; however, it was still statistically significant

(*p* = 0.01). Furthermore, 4 WBV studies included in this analysis involved some component (lunges, squats) of RT. Therefore, it is unclear if this RT component contributed to the overall improvements. Removing these studies from the analysis yields a lower overall effect (SMD = 0.59 (0.30–0.87), which is statistically still significant (*p* = 0.03); however, with this reduction in studies, the subgroup analyses indicate statistically significant difference (*p* = 0.001) between RT and WBV, indicating the superiority of RT compared to WBV without any RT components. Additionally, we repeated the analysis with exclusion of RT studies on sarcopenia patients (SMD increased from 1.24 to 1.34) and vice versa (SMD dropped to 1.01). Therefore, a slight tendency for larger effect in healthy older adults was indicated. A final sensitivity analysis was performed for type of measurement. Removing the studies that measured isokinetic strength increased the main effect slightly (from 1.24 to 1.33). However, the studies with isokinetic measurements also had large and statistically significant pooled effect (SMD = 0.88; *p* < 0.001), which suggest isokinetic and isometric strength both substantially increased with RT.

Leg press strength was reported in 5 RT studies (8 interventional groups) [46,60,61,68,69]. There was a statistically significant increase in intervention groups across studies (SMD = 1.45 (0.85–2.06); *p* < 0.001; I<sup>2</sup> = 83%) (Figure 3). Interventions performed 3 times per week tended to have a larger effect (SMD = 1.98 (0.50–3.45)) than interventions performed 2 times per week (SMD = 1.12 (0.78–1.47)), but the subgroup difference was not statistically significant (*p* = 0.27 for subgroup differences). Two RT studies reported back extensor strength [45,70] and showed a statistically significant increase (MD = 7.97 kg (3.07–12.88 kg); *p* < 0.001; I<sup>2</sup> = 0.0%) (Figure 3). Three RT studies [71–73] reported a composite score for strength (i.e., sum of several strength tasks). There was a statistically significant improvement in intervention groups (SMD = 3.55 (2.28–4.83); *p* < 0.001; I<sup>2</sup> = 90%) (Figure 3). Grip strength was reported in 19 RT studies [44,45,49,52,53,55,56,59,61,65,67,69,70,74–79]. There was a mean increase of 1.48 kg (0.26–2–23 kg; *p* < 0.001) across studies with pre-post mean differences ranging from −1.00 to 5.70 kg.

#### *3.5. E*ff*ects of RT on Body Composition*

Muscle mass was reported in 7 RT studies (8 intervention groups) [45,52,70,71,74,78,80]. Compared to control groups, there was not a statistically significant increase in muscles mass in intervention groups across studies (MD <sup>=</sup> 0.60 kg (−0.18–1.37 kg); *<sup>p</sup>* <sup>=</sup> 0.13; I<sup>2</sup> <sup>=</sup> 83%) (Figure 4). There were no differences between interventions performed 2 times a week (MD = 0.60 kg (−1.01–2.22 kg)) and 3 times a week (MD = 0.68 kg (0.23–1.14 kg)) (*p* = 0.93 for subgroup differences). Appendicular muscle mass was reported in 7 RT studies [51–53,65,70,80–82]. The pooled effect showed no change after RT interventions compared to control groups (MD <sup>=</sup> 0.01 kg (−0.26–0.28 kg); *<sup>p</sup>* <sup>=</sup> 0.92; I<sup>2</sup> <sup>=</sup> 8%) (Figure 4). Lower-limb muscle mass was reported in 8 RT studies [51–53,55,56,67,80,82], with an overall small and statistically non-significant increase (MD <sup>=</sup> 0.18 kg (−0.11—0.47 kg); *<sup>p</sup>* <sup>=</sup> 0.22; I<sup>2</sup> <sup>=</sup> 45%) (Figure 4). No statistically significant differences were shown between interventions performed 3 times per week (MD = 0.55 kg (−0.44–1.55 kg)) compared to interventions performed 2 times per week (MD = 0.10 kg (−0.10–0.31 kg)) (*p* = 0.39 for subgroup differences). Upper limb muscle mass was reported in 5 RT studies [53,56,67,80,82], and the pooled effect was negligible (MD = 0.01 kg (−0.11–0.13 kg); *p* = 0.84; I<sup>2</sup> = 0%) (Figure 4).


**Figure 3.** Effect of resistance exercise interventions on back extension, leg press, and composite strength scores.

**Figure 4.** Effect of resistance exercise interventions on muscle mass.

Fat-free mass was recorded in 2 WBV [39,83], 7 RT [55,62,73–76,81], and 1 EMS studies [84], with a very small and statistically non-significant reduction across studies (MD = −0.27 kg (−0.84–0.31 kg); *p* = 0.46; I<sup>2</sup> = 0%). The pooled effect of the two WBV studies showed a slight increase (MD = 0.53 kg (−1.75–2.81 kg); *p* = 0.15), as did one EMS study (MD = 0.61 kg (−0.81–2.03 kg); *p* = 0.40), while there was a small and statistically non-significant decrease across RT interventions (MD = −0.60 kg

(−1.28–0.09 kg); *p* = 0.09). The differences between WBV, RT, and EMS were not statistically significant (*p* = 0.25).

Body fat mass was reported in 2 WBV [39,41] and 14 RT (16 intervention groups) studies [45,50,53,55,58,62,70,71,73,74,76,80,81,85], with a statistically significant decrease overall (SMD <sup>=</sup> <sup>−</sup>0.65 (−1.09–−0.21); *<sup>p</sup>* <sup>&</sup>lt; 0.001; I<sup>2</sup> <sup>=</sup> 86%). For the purposes of MD calculation, three studies (4 intervention groups) [45,58,74] that reported body mass in kg instead of the percentage of body weight were removed and the analysis was repeated. SMD slightly increased (SMD = −0.74) and MD calculation showed a mean reduction of body fat mass percentage of −1.99% (−3.75–−0.22%).

Nine RT studies [44,50,67,70,74,77,78,82] and one EMS study [86] also reported the sarcopenia index (sometimes termed skeletal muscle index) (Figure 5). Mainly (7 studies), the index was computed as the ratio of appendicular skeletal muscle mass and the square body height. However, since two studies did not report the exact calculation of the index, we opted for SMD in order analyses to be conservative. There was a moderate, but statistically non-significant improvement across all studies (SMD <sup>=</sup> 0.65 (−0.02–1.32); *<sup>p</sup>* <sup>=</sup> 0.06; I<sup>2</sup> <sup>=</sup> 90%). Subgroup analyses favored RT interventions, performed 2 times weekly (*p* = 0.008); this is being heavily influenced by one RT study that showed substantial improvement (SMD = 3.44). Most of the studies showed very small negative or very small positive effects, while the pooled effect was heavily influenced by the aforementioned study. Furthermore, 3 WBV studies [42,87,88] (5 intervention groups) and 3 RT studies [47,62,66] reported the quadriceps muscle (or individual heads of quadriceps muscle) cross-sectional area. In order to obtain a sufficient number of studies for meaningful comparison, these results were compared together and expressed as SMD. Overall, there was a statistically significant effect of interventions (SMD = 0.29 (0.03–0.55); *p* = 0.03; I<sup>2</sup> = 0%) (Figure 5). Subgroup differences showed no differences between RT (SMD = 0.61 (0.04–1.18)) and WBV (SMD = 0.20 (−0.09–0.49) (*p* = 0.21 for subgroup differences). For the RT studies (all reported the cross-sectional area for the full quadriceps muscle), the MD was 1.80 (0.51–3.09) cm<sup>2</sup> . One RT study [57] reported thigh circumference, with no effect of the intervention (MD = −0.10 cm (−2.55–2.35 cm); *<sup>p</sup>* <sup>=</sup> 0.94; I<sup>2</sup> not applicable).

Two RT studies [58,89] reported the percentage of type I fibers, with small and statistically non-significant pooled effect (MD <sup>=</sup> 0.14% (−1.38–1.66%); *<sup>p</sup>* <sup>=</sup> 0.86; I<sup>2</sup> <sup>=</sup> 0%). The same two studies reported the percentage of type IIa fibers, showing slight but statistical non-significant increase (MD = 1.03% (−0.43–2.48%); *<sup>p</sup>* <sup>=</sup> 0.17; I<sup>2</sup> <sup>=</sup> 11%). Finally, one RT study [58] reported a statistically significant increase in the percentage of type IIx fibers (MD = 2.42% (1.96–2.88); *p* < 0.001; I<sup>2</sup> not applicable).

#### *3.6. E*ff*ects of RT and WBV on Body Functional Performance*

The results on functional performance are summarized in Figure 6. The timed up-and-go test was performed in 2 WBV [87,88] and 6 RT studies [52,55,69,75,90]. Overall, there were no differences between intervention and control groups across all studies (MD <sup>=</sup> <sup>−</sup>0.12 s (−1.36–1.12 s); *<sup>p</sup>* <sup>=</sup> 0.85; I<sup>2</sup> <sup>=</sup> 93%). There were also no differences between the WBV and RT (MD = 0.20 and −0.08 s, respectively; *p* = 0.89 for subgroup differences). The 30-s sit-stand test was performed in 6 RT studies [55,59,68,76,80,85], with an overall improvement of 2.68 repetitions (1.90–3.47 repetitions, *p* < 0.001; I<sup>2</sup> = 0.50%). There was no difference between interventions performed 2 times per week (MD = 2.85 (1.16–4.54 repetitions)) and 3 times per week (MD = 2.73 (2.07–3.39 repetitions)) (*p* = 0.90 for subgroup differences). The 5-repetition sit-stand test was recorded in 4 RT studies [65,67,75,76], and there was a significant improvement (i.e., decreased time to complete the test) across all studies (MD <sup>=</sup> <sup>−</sup>2.36 s (−3.9–−0.82 s); *<sup>p</sup>* <sup>=</sup> 0.003; I<sup>2</sup> <sup>=</sup> 83%).


**Figure 5.** Effects of whole-body vibration and resistance exercise on sarcopenia index and quadriceps cross-sectional area.


**Figure 6.** Effects of whole-body vibration and resistance exercise on functional mobility tests.

#### **4. Discussion**

The purpose of this systematic review with meta-analysis was to investigate the effects of RT, WBV, and EMS interventions on muscle strength, body composition, and functional performance in older

adults. It included randomized controlled trials involving at least one intervention group (RT, EMS, or WBV) and a control group were included. In total, 64 studies were included in the meta-analysis (48 RT studies, 12 WBV studies, and 4 EMS studies). The main findings of the present systematic reviews are: (1) knee extension strength was improved by RT and WBV, but not ES; (2) the remaining strength outcomes were only assessed in RT studies and significant positive effects were observed; (3) the effects of RT on body composition were small, while the effects of WBV and EMS are unclear due to the small number of studies; (4) there were small effects on sarcopenia index, while quadriceps cross-sectional area was improved in RT studies, but not WBV studies; (5) functional performance was improved by RT interventions, though not in all tests. Overall, the RT interventions proved to be effective for improving muscle strength, muscle cross-sectional area and functional performance, while the effects on body composition were small or non-existent. WBV seems to be comparably effective for improving muscle strength, but not muscle cross-sectional area. A major limitation of the review is the smaller number of WBV and particularly EMS studies. Comparisons between the different intervention types were therefore limited and were not possible for several outcome measures. Subgroup analyses revealed that some of the independent variables (duration of intervention, weekly frequency, type of resistance in RT studies, and age of participants) might have influenced the results; however, these findings were not statistically significant and cannot be conclusively confirmed.

The positive effects of RT, WBV, and EMS in older adults have been reported numerous times [9–11,13,14,19,22,23,25,26,30,31,91–93]. In this review, we included only randomized controlled trials that included at least one group that did not receive any interventions (control group). While the positive effects of RT were clearly demonstrated, the effects of WBV, and in particular EMS, were smaller or absent. Individual studies that directly compared RT and WBV have shown similar effects of the two interventions related to muscle strength and power outcomes [25,26]. In a non-controlled single-group study, improvements in muscle strength and power and functional performance were also observed after 9 weeks of WBV [94]. While the present review showed improvements in muscle strength after WBV interventions, only 2 WBV studies that assessed functional performance were included. Therefore, the effects of WBV on functional performance remain unclear. Since improvements in functional performance are often observed in parallel with increases in muscle strength [92,95,96] and muscle power [97], it can be expected that WBV will also increase functional performance. In addition to increases on muscle strength and possible improvements in functional performance after WBV, previous research also showed positive effects of WBV on postural balance [22], cardiovascular outcomes [98] and possibly muscle activation [99] in older adults. Overall, we can recommend the prescription of WBV to older adults, but it cannot be guaranteed that WBV will produce comparable effects to RT in view of all outcomes relevant to health and well-being.

EMS has been used extensively in people who cannot engage in normal physical activity and has been shown to produce somewhat similar responses to exercise at the muscular level [100]. In this review, a very limited amount of randomized controlled trials has been identified to investigate the effects of EMS in older adults. Our analyses could not confirm or indicate any effects of EMS interventions. EMS has previously been shown to be effective in counteracting muscle weakness in advanced disease [101] and sarcopenia in older adults [30,32], and even to provide additive effects in terms of morphological outcomes when combined with RT in healthy adults [102]. However, the effect of EMS on functional performance of the older adults are less consistent [103]. Nevertheless, the above-mentioned promising results should be re-evaluated in randomized controlled trials to strengthen the findings and enable better comparison to RT and WBV. Based on the results of this and previous research [92], the use of EMS should be encouraged when performing physical activities is not possible or older adults are not motivated to perform it.

Across all interventions, the improvements in muscle strength were much more evident than improvements in muscle mass. It is known that improvements in strength due to neural adaptations occur much earlier before a meaningful increase in muscle mass is seen [104]. While most of the interventions in the present review lasted 12 weeks or longer, improvements in muscle mass could

nonetheless be expected. It is possible that muscle mass measurements are not reliable enough to detect the effect of the interventions. Alternatively, the cross-sectional area of the quadriceps was statistically significantly increased across RT studies in this review. Moreover, a previous review also reported notable increases in the cross-sectional area of thigh muscles (+2.31 cm<sup>2</sup> ) in older adults aged >75 years [105]. Interestingly, the latter review reported such effects for WBV, while the pooled effects of the WBV studies in our review were small.

The results on functional performance were different across outcome measures. Neither WBV, RT nor EMS improved the performance of the timed up-and-go test. Conversely, the sit-stand performance was significantly improved by RT interventions (an increase of 2.68 repetitions in 30-s sit-stand task and a decrease of 2.36 s in the 5-repetition sit-stand task time). It should be noted that the results regarding functional performance were significantly influenced by the heterogeneity of the studies. In particular, the timed up-and-go test performance was substantially improved (−1.77 s) in one study and reduced even more in the second study (+1.99 s). Similarly, most RT studies showed improvements in this test, but one study [69] showed a large reduction (+3.6 s), which led to a negligible pooled effect. This particular study was conducted on very old participants (> 90 years) and included a short-term resistance exercise program, based on light to moderate loads. If this study is excluded from the analysis, the pooled effect size would show statistically significant positive improvements (MD = −0.93 s; *p* < 0.001).

The secondary aim of this paper was to determine the independent variables, related to the interventions, that can influence the magnitude of the outcomes. Most of the subgroup analyses that could be conducted as the number of studies was sufficient, showed no such statistically significant effects. There were statistically non-significant trends for lower limb muscle mass and leg press strength to be improved more with a higher (≥3) weekly session frequency. The literature in the field of sports science [106,107] suggests that weekly frequency is not an independent factor for improvements in muscle strength and muscle mass. A recent meta-analysis suggested that similar is true for older adults [108], although a minimum of 2 sessions per week is typically recommended. Our results also indicated a potentially higher effect of interventions based on machine training and free weights, compared to elastic resistance and approaches combining several types of resistance. In the general population, the effect of elastic resistance appears to be essentially the same as machine-based resistance and free weights [109]. Note that our observation on lesser effects of elastic resistance compared to machines and free weights is limited to knee extension strength and that the difference between the effect of elastic resistance (SMD = 0.91) and machine-based resistance (SMD = 1.36) and free weights (SMD = 1.33) was not statistically significant (*p* = 0.68). Therefore, it is probably appropriate to include elastic resistance in RT programs for older adults.

The first limitation of this systematic review with meta-analysis is the inclusion of only randomized controlled trials. While this was done to compile only high-quality evidence, important findings from studies with different designs were omitted. In particular, the number of EMS studies was very small. It should be emphasized that the lack of reported effects of EMS in the review is partly due to the lack of randomized controlled trials and not necessarily because the EMS is not effective. Furthermore, a major limitation of the review is the high heterogeneity of the studies, which precluded more subgroup analyses and is potentially a major confounding factor. Partially, we investigated this issue with several sensitivity analyses which showed that the results were not heavily influenced by certain factors, such as type of measurements (for knee strength), presence of sarcopenia (though somewhat smaller effects were observed in elderly sarcopenia patients), and adherence to studies. Because there are several factors that can influence response to resistance exercise (in particular, the characteristics of the intervention in addition to those mentioned above), we did our best to perform subgroup analyses to exclude or confirm several factors, such as exercise frequency, intervention duration, and resistance exercise type. Nevertheless, some of the variability between the interventions could not be accounted for. Therefore, we strongly emphasize that these results should be viewed with high caution. Future

studies and practitioners should not use the numbers we obtained as a standalone guideline, but rather view our analyses as an exploration of general trends in the field of interventions for older adults.

#### **5. Conclusions**

This paper reviewed RCT studies that examined the effects of RT, WBV, and EMS on muscle strength, body composition, and functional performance of older adults. It was found that RT and WBV are effective for increasing muscle strength, while the data was very limited for EMS. RT interventions also improve functional performance and increase muscle-cross sectional area but have no effect on muscle mass. Further studies exploring the effect of WBV and in particular of EMS are needed for better comparison with RT. For the time being, EMS can be recommended for people that are unable to perform RT or WBV. Otherwise, RT or a combination of RT and WBV or EMS is probably the most efficient way to improve muscle strength and functional performance, while the best approach to increase muscle mass in older adults still needs to be determined by further studies. Due to the several limitations of this review, we urge the readers to view the results with caution.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/9/2902/s1, Supplementary data 1: Detailed data regarding study outcomes, interventions and participants.

**Author Contributions:** Conceptualization, N.S. and Ž.K.; methodology, N.Š., Ž.K., S.L., C.H.; software, Ž.K.; formal analysis, N.Š., Ž.K., S.L., C.H.; investigation, N.Š., Ž.K., S.L., C.H.; resources, N.S., S.L.; data curation, N.Š., Ž.K., S.L., C.H.; writing—original draft preparation, N.Š., Ž.K.; writing—review and editing, S.L., C.H.; visualization, N.Š, Ž.K.; supervision, N.S.; project administration, N.Š. funding acquisition, S.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** The study was supported by Institute for Physical Medicine and Rehabilitation, Physiko- & Rheumatherapie GmbH.

**Acknowledgments:** We want to acknowledge the support of the European Regional Development Fund and Physiko- and Rheumatherapie institute through the Centre of Active Ageing project in the Interreg Slovakia-Austria cross-border cooperation program (partners: Faculty for Physical Education and Sports, Comenius University in Bratislava: Institute for Physical Medicine and Rehabilitation, Physiko- & Rheumatherapie GmbH). Authors NS and ZK acknowledge the European Commission for funding the InnoRenew CoE project (Grant Agreement 739574) under the Horizon2020 Widespread-Teaming program.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


skeletal muscle in sarcopenic or dynapenic older adults. *Geriatr. Gerontol. Int.* **2019**, *19*, 429–437. [CrossRef] [PubMed]


mass in old institutionalized adults: A randomized, multi-arm parallel and controlled intervention study. *Eur. J. Phys. Rehabil. Med.* **2018**, *54*, 921–933. [CrossRef] [PubMed]


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **E**ff**ect of Aerobic Exercise Training and Deconditioning on Oxidative Capacity and Muscle Mitochondrial Enzyme Machinery in Young and Elderly Individuals**

**Andreas Mæchel Fritzen 1,2,\* , Søren Peter Andersen <sup>1</sup> , Khaled Abdul Nasser Qadri <sup>1</sup> , Frank D. Thøgersen <sup>1</sup> , Thomas Krag <sup>1</sup> , Mette C. Ørngreen <sup>1</sup> , John Vissing <sup>1</sup> and Tina D. Jeppesen <sup>1</sup>**


Received: 31 August 2020; Accepted: 23 September 2020; Published: 26 September 2020

**Abstract:** Mitochondrial dysfunction is thought to be involved in age-related loss of muscle mass and function (sarcopenia). Since the degree of physical activity is vital for skeletal muscle mitochondrial function and content, the aim of this study was to investigate the effect of 6 weeks of aerobic exercise training and 8 weeks of deconditioning on functional parameters of aerobic capacity and markers of muscle mitochondrial function in elderly compared to young individuals. In 11 healthy, elderly (80 ± 4 years old) and 10 healthy, young (24 ± 3 years old) volunteers, aerobic training improved maximal oxygen consumption rate by 13%, maximal workload by 34%, endurance capacity by 2.4-fold and exercise economy by 12% in the elderly to the same extent as in young individuals. This evidence was accompanied by a similar training-induced increase in muscle citrate synthase (CS) (31%) and mitochondrial complex I–IV activities (51–163%) in elderly and young individuals. After 8 weeks of deconditioning, endurance capacity (−20%), and enzyme activity of CS (−18%) and complex I (−40%), III (−25%), and IV (−26%) decreased in the elderly to a larger extent than in young individuals. In conclusion, we found that elderly have a physiological normal ability to improve aerobic capacity and mitochondrial function with aerobic training compared to young individuals, but had a faster decline in endurance performance and muscle mitochondrial enzyme activity after deconditioning, suggesting an age-related issue in maintaining oxidative metabolism.

**Keywords:** aerobic exercise training; mitochondria; sarcopenia; endurance; deconditioning; skeletal muscle; elderly

#### **1. Introduction**

Age-related loss of muscle mass and function, referred to as sarcopenia, is an inevitable process, affecting more than 40% of individuals above 80 years of age [1]. Sarcopenia and reduced aerobic capacity in elderly individuals are strong mediators of morbidity [2] and mortality [3,4]. The ability to perform activities of daily living in healthy individuals is progressively reduced with age, seemingly associated with a decrease in aerobic capacity [5]. Lower levels of aerobic capacity can contribute to a loss of independence, increased incidence of disability, frailty, and reduced quality of life in older

people. Sarcopenia and age-related impaired aerobic capacity are related to a multitude of factors, including muscle mitochondrial degeneration [6,7].

It is well established that aerobic exercise training increases maximal aerobic exercise capacity (VO2peak), accompanied by improvements in mitochondrial content, function, and enzyme expression in young, untrained individuals [8–11]. In elderly, findings have been equivocal. Some studies found that 6–16 weeks of intense aerobic exercise training improved aerobic capacity and mitochondrial enzyme activity [12–17], while others were not able to confirm significant effects of training in elderly [18–20]. Thus, it is unclear whether elderly have an attenuated response to training in aerobic capacity compared with young individuals [13,21,22]; in particular, it is not fully understood whether the plasticity for mitochondrial adaptations to aerobic training occurs to the same extent in young and elderly individuals.

A training-induced increase in muscle mitochondrial content and enzyme activity were shown to return to baseline with as little as 4–8 weeks of deconditioning in healthy, young individuals [23–27]. Thus, aerobic training and deconditioning are effective ways to provoke mitochondrial plasticity. In elderly, it could be hypothesized that the age-associated impairments in aerobic capacity and muscle mitochondrial function could relate to relatively faster loss of mitochondrial capacity with deconditiong, but the effect of deconditioning on mitochondrial content and enzyme activity has never been studied in elderly.

Mitochondria are important for many vital functions of the cell, including being a key initiator of programmed cell death (apoptosis). Studies in rats showed an increased apoptotic activity in the aging muscle, accompanied by a lowered expression of the mitochondrial outer membrane antiapoptotic B-cell lymphoma 2 (Bcl2) protein, which was reversed by 12 weeks of aerobic training [28–30]. Furthermore, cleavage of cysteine-dependent, aspartate-specific protease-3 (caspase-3), indicative of increased activation of caspase-3, is a key factor in induction of apoptosis, and it was found to be increased in skeletal muscle of 24-month-old compared to 12-month-old rats [31]. Collectively, these findings in rodents led to the idea that increased apoptotic activity driven by mitochondria could be a contributing mediator of age-related muscle loss in humans that can be reversed by exercise training [32]. These data imply that mitochondria-driven apoptosis could be a key factor behind age-related muscle function and mass loss. However, studies investigating mitochondrial and apoptotic biomarkers in skeletal muscle of elderly in response to aerobic training and deconditioning—and, thus, potential explanation for age-related muscle mass—are scarce.

The aim of this study was to investigate the effect of aerobic training and deconditioning on aerobic capacity and muscle mitochondrial function in elderly (>75 years old) and young healthy individuals (age < 30 years old). We hypothesized that elderly individuals would have indices of mitochondrial dysfunction, but that elderly would increase their aerobic and endurance capacity, as well as measures of mitochondrial content and function, to the same extent as the young individuals after aerobic training.

#### **2. Materials and Methods**

#### *2.1. Individuals*

The aim was to include a minimum of 10 elderly healthy individuals (age above 75 years old) and 10 healthy young individuals at the age of 20 to 30 years old. Exclusion criteria were nonsedentary, illness that required medication other than antihypertensive and antithrombotic treatment, severe musculoskeletal pain, neurological disorder, smoking, cardiovascular disease, attendance rate below 80% of total training sessions, additional training during the training phase, or failure to comply with instructions of inactivity during the deconditioning phase. Sedentary was defined as performing less than one hour of exercise a week at low to moderate intensity or a maximum of 5 km of cycling for transportation a day.

All participants completed a detailed medical history and electrocardiography, and all had a normal neurological examination before entering the study.

In total, 21 healthy individuals, 11 elderly (four women and seven men; 80 ± 4 years) and 10 young (five women and five men; 24 ± 3 years) individuals were included in the study. Every included participant completed the study in full.

All individuals gave oral and written consent to participate according to the Helsinki declaration. The study was approved by the Ethics Committee of the Capital Region (No. KF-293615). The individuals were all informed about the nature and risks of the study and gave written consent to participate before inclusion.

#### *2.2. Study Design*

The 11 elderly and 10 young participants completed a 6 week aerobic exercise training intervention on a bicycle ergometer followed by 8 weeks of deconditioning (Figure 1). Maximal aerobic exercise capacity (VO2peak) and maximal workload were evaluated by an incremental test and aerobic endurance capacity evaluated by a time-to-exhaustion test at 80% of pretraining maximal workload before and after aerobic exercise training, and again after 4 and 8 weeks of deconditioning. Skeletal muscle biopsies were taken from vastus lateralis muscle before and after aerobic exercise training and after 8 weeks of deconditioning for measurement of mitochondrial and apoptotic markers. Dual-energy X-ray absorptiometry (DEXA) scanning of body composition was performed at baseline.

**Figure 1.** Study design overview. Twenty-one participants completed a 6 week aerobic exercise training intervention followed by 8 weeks of deconditioning (detraining—no exercise). Maximal aerobic exercise capacity and aerobic endurance capacity were evaluated using a maximal oxygen consumption rate test and an endurance time-to-exhaustion test, respectively, before and after aerobic exercise training and after subsequent 4 and 8 weeks of deconditioning. Skeletal muscle biopsies were taken from vastus lateralis muscle at baseline, after 6 weeks of aerobic training and after 8 weeks of deconditioning. DEXA: Dual-energy X-ray absorptiometry, VO2peak: Peak oxygen consumption rate.

#### *2.3. DEXA Scanning*

A whole-body dual-energy X-ray absorptiometry (DEXA) scan (GE Medical Systems, Lunar, Prodigy, Chicago, IL) was performed prior to the intervention. Elderly and young individuals were instructed to drink 2.5 L of liquid and, hence, be well hydrated the day before the DEXA scan. They arrived overnight-fasted and were encouraged to empty their bladder prior to the scan. They underwent the DEXA scan by lying straight and centered on the table with the hip region within two sets of hash marks on either side of the long edge of the table to ensure the entire body was within the scan area according to the manufacturer's instructions. The images were analyzed using enCORE™2004 Software (v.8.5) (GE Medical Systems, Lunar, Prodigy, Chicago, IL, USA). Reliability of this DEXA scanning procedure was recently described [33].

#### *2.4. Maximal Oxygen Consumption Test*

Before initial testing, individuals were familiarized with the equipment and test protocol on a separate day with a training session to reduce the impact that skill learning has on strength performance.

On each test day, individuals carried out an incremental cycling test to exhaustion on a stationary bicycle (Monark 939E, Sweden), and VO<sup>2</sup> was measured by pulmonary gas exchange with a breath-by-breath gas analyzer using an open-circuit online respirometer for indirect calorimetry measurements (Cosmed, Quark B2, Pavona, Italy). Load was set individually, increasing every other minute for the first 10 min, and thereafter every minute until exhaustion. Heart rate (HR) was measured during exercise, and the subject's self-assessed feeling of exertion, on a Borg scale, was assessed every minute. Maximal workload (Wmax) was the maximal power output (in Watt) achieved and sustained for at least 1 min during the incremental test.

#### *2.5. Endurance Test*

After the incremental test, individuals rested for 1 h before carrying out an endurance test on a stationary bicycle (Monark 939E, Sweden) evaluating time to exhaustion at 80% of pretraining Wmax, obtained under the test for maximal oxygen consumption. Exhaustion was achieved when individuals could not maintain a self-chosen pedal cadence rpm minus 10 rpm for 10 s (e.g., if a chosen rpm at 70 dropped to less than 60 rpm for more than 10 s, exhaustion was achieved). During this test, VO<sup>2</sup> was measured by pulmonary gas exchange as described above, and HR was also measured continuously throughout the test. Exercise economy during the endurance test was calculated as average VO<sup>2</sup> during the test divided by the workload (Watt).

#### *2.6. Aerobic Exercise Training and Deconditioning Interventions*

During the 6 week aerobic exercise training intervention, volunteers trained four times per week on a cycle ergometer. Each session lasted 35 min, and sessions alternated between continuous exercise bouts and intermittent exercise bouts. Continuous exercise sessions involved 35 min of continuous cycling at an intensity of 70% of the maximal heart rate (HRmax) reserve (the dynamic area between the resting HR (HRrest) and HRmax). Intermittent exercise consisted of 5 × 4 min intervals at an intensity of 95% of HRmax reserve, with 3 min of rest between intervals.

HRmax reserve has been shown to be well correlated to the intensity as percentage of VO2peak. Heart rate intervals were estimated using the following formula, described by Swain et al. (2000) [34]:

HR% intensity = (HRmax − HRrest) × Intensity (%) + HRrest.

Heart rate intervals were set to the calculated HR ± 5 bpm. Training was carried out in a progressive manner, with an increasing workload during the training period to achieve the determined HR intervals. All training sessions were supervised to ensure correct exercise intensity and were carried out on stationary bikes (Monark 939E, Sweden or Tunturi T6, Finland). Heart rate was recorded during exercise by a heart-rate monitor. After 6 weeks of aerobic training, participants stopped the training program and returned to their habitual sedentary lifestyle and were instructed not to initiate any new form of training for the following eight weeks. Individuals wore a step counter during the entire study, i.e., the training and deconditioning period, to ensure that the level of daily activity during the training period corresponded to the activity level of the deconditioning period. Step counters were checked once per week throughout the period to ensure that the physical activity level did not vary more than 10% on a weekly basis.

#### *2.7. Skeletal Muscle Biopsies*

A skeletal muscle biopsy was performed after the endurance test in vastus lateralis right leg muscle pre- and post-training and after 8 weeks of deconditioning within 15 min of the endurance test. The biopsy was performed as previously described using a 5 mm percutaneous Bergström needle [35]. Needle entry was at least 3 cm away from the previous insertion to avoid scar tissue and interference with data due to post-biopsy edema. Muscle samples were immediately frozen in liquid isopentane cooled by liquid nitrogen before storage at −80 ◦C for later analysis.

#### *2.8. Mitochondrial Enzyme Activities*

Citrate synthase (CS) and mitochondrial complex I–IV enzyme activities were determined as previously described [23,36]. Muscle tissue was homogenized in 19 volumes of ice-cold medium containing protease and phosphatase inhibitor cocktail. Enzyme assays for CS and complex I–IV were performed at 25 ◦C in a Lambda 16 spectrophotometer (Perkin Elmer) [37]. Complex I specific activity was measured by following the decrease in absorbance due to the oxidation of nicotinamide adenine dinucleotide (NADH) at 340 nm with 425 nm as the reference wavelength. Sample was added to a buffer containing 25 mM potassium phosphate (pH 7.2), 5 mM MgCl2, 2 mM KCN, 2.5 mg/mL antimycin A, 0.13 mM NADH, 0.1 mg/mL sonicated phospholipids, and 75 µM decylubiquinone. Complex I activity was measured 3–5 min before addition of 2 µg/mL rotenone, after which the activity was measured for an additional 3 min. Complex I activity was the rotenone-sensitive activity [37,38]. Complex II specific activity was measured by following the reduction of 2,6-dichlorophenolindophenol (DCPIP) at 600 nm. Samples were preincubated in buffer containing 25 mM potassium phosphate (pH 7.2), 5 mM MgCl2, and 20 mM succinate at 30 ◦C for 10 min. Antimycin A (2 µg/mL), 2 µg/mL rotenone, 2mM KCN, and 50 µM DCPIP were added, and a baseline rate was recorded for 3 min. The reaction was started with decylubiquinone (50 µM), and the enzyme-catalyzed reduction of DCPIP was measured for 3–5 min [37,38].

Complex III specific activity was determined in a reaction mixture containing the sample and 100 µM ethylenediaminetetraacetic acid (EDTA), 0.2% defatted bovine serum albumin (*w*/*v*), 3 mM/L sodium azide, and 60 µM/L ferricytochrome c in 50 mM/L potassium buffer (pH 8.0). The reaction was started by addition of 150 µM decylubiquinol in ethanol and monitored for 2 min at 550 nm [39]. Complex IV activity was measured by following the oxidation of cytochrome c (II) at 550 nm with 580 nm as the reference wavelength. The reaction buffer contained 20 mM potassium phosphate (pH 7.0) and 15 µM cytochrome c (II). Sample was added to the reaction buffer, and the initial activity was calculated from the apparent first-order rate constant after fully oxidizing cytochrome c [37,38].

CS activity was measured following the NADH changes at 340 nm at 25 ◦C by 50-fold dilution in a solution containing 100 µM acetoacetyl-CoA, 0.5 mM NAD (free acid), 1 mM sodium malate, 8 µg/mL malate dehydrogenase, 2.5 mM EDTA, and 10 mM Tris-HCl (pH 8.0). Samples were preincubated with 0.25% Triton X-100.

#### *2.9. Western Blotting Analysis*

Western blot analysis was performed as previously described [23,40]. For Western blotting, biopsies were sectioned on a cryostat (Microm HM550, Thermo Fisher Scientific, Waltham, MA, USA) at −20 ◦C and homogenized in ice-cold lysis buffer mixed with sample buffer. Proteins were separated on an SDS-PAGE gel, blotted to polyvinylidene difluoride (PVDF) membranes, and incubated in primary and secondary antibodies. Antibodies were directed toward Bcl2 (diluted 1:5000; Cell Signalling Technologies, Beverly, MA, USA) and alpha-tubulin (diluted 1:30.000; Abcam, UK, no 4074), with alpha-tubulin used as a loading control. Secondary goat anti-rabbit and goat anti-mouse antibodies coupled with horseradish peroxidase at a concentration of 1:10,000 were used to detect primary

antibodies (DAKO, Glostrup, Denmark). Immunoreactive bands were detected by chemiluminescence using Clarity Max, (BioRad), quantified using a GBox XT16 darkroom, and GeneTools software was used to measure the intensities of immunoreactive bands (Syngene, Cambridge, UK). Immunoreactive band intensities were normalized to the intensity of the alpha-tubulin bands for each participant to correct for differences in total muscle protein loaded on the gel.

#### *2.10. Bioplex Analysis*

Muscle tissue was homogenized in the same way as described above (see Western blotting analysis). The prepared homogenates were diluted to a final protein concentration of 400 µg/mL. The Human Apoptosis 3-plex Panel (Invitrogen, CA, USA) was used for protein quantification of cleaved caspase-3 (cl. caspase-3) and a single-plex magnetic bead assay for beta-tubulin (loading control) (Millipore, Merck KGaA, Darmstadt, Germany). Then, 100 µL of prepared standards were added to separate wells and incubated at room temperature in the dark for 2 h. The plate was washed twice, before adding a 1× detection antibody to the wells, and then incubated for 1 h in darkness at room temperature. The plate was again washed twice, and 50 µL of streptavidin-R-Phycoerythrin (RPE) was added to the wells, followed by 30 min of incubation. The plate was washed three times, and 130 µL of wash solution was added to each well, upon reading the plate on a Luminex Bio-plex 200 system (Biorad, Hercules, CA, USA).

#### *2.11. Statistical Analysis*

All statistical analyses were carried out using SigmaPlot 11.0 and GraphPad PRISM 8 (GraphPad, La Jolla, CA, USA). All data are expressed as the mean ± standard error of mean (SE), except for baseline anthropometric characterization of participants shown as mean ± standard deviation (SD) (Table 1). A Shapiro–Wilk test was performed to test for normal distribution of data. The differences among groups were analyzed by a repeated-measures two-way analysis of variance (ANOVA) followed by Tukey's multiple comparison tests, when ANOVA revealed significant interactions. Baseline subject characteristics were evaluated with unpaired *t*-tests between young and elderly groups. Correlation analyses were performed with the Pearson's product-moment correlation coefficient. Differences were considered statistically significant when *p* < 0.05.


**Table 1.** General demographic data.

BMI, body mass index; FFM, fat-free mass; FM, fat mass, VO2peak, maximal oxygen consumption rate. Data are shown as means ± SD. *n* = 10 in young and *n* = 11 in elderly. \*/\*\*/\*\*\* Significantly different (*p* < 0.05/0.01/0.001) from young group.

#### **3. Results**

#### *3.1. Anthropometry*

Height, total body weight, and fat-free mass were similar among the young and the elderly individuals, whereas the elderly had a higher BMI (+15%), fat mass (+40%), and body fat% (+31%) and a lower VO2peak (−40%) compared with the young individuals (*p* < 0.05; Table 1).

#### *3.2. Functional Parameters of Aerobic Capacity*

The elderly individuals had lower absolute values of VO2peak (~40%) and Wmax (~60%) compared with the young individuals (*p* < 0.001; Figure 2A,B). Six weeks of aerobic training improved VO2peak and Wmax by 13% and 34%, respectively, in elderly individuals (*p* < 0.05) and to the same extent by 9% and 26%, respectively, in young individuals (*p* < 0.05) (Figure 2A,B). VO2peak was lowered by 13% already after 4 weeks of deconditioning in the elderly only (*p* < 0.05), and VO2peak returned to baseline in both the elderly and the young individuals after 8 weeks of deconditioning (Figure 2A). In the elderly individuals, Wmax also returned to pretraining level after 8 weeks of deconditioning, while Wmax was still increased by 11% in the young individuals compared with pretraining level (*p* < 0.05; Figure 2B). Endurance capacity, measured as time to exhaustion on 80% of pretraining Wmax, was improved to a similar extent by 2.4- and 1.5-fold in elderly and young individuals (*p* < 0.05), respectively (Figure 2C). Endurance capacity was impaired by 20% and 25% in the elderly by 4 and 8 weeks of deconditioning, but remained at post-training levels in the young individuals during deconditioning (Figure 2C).

**Figure 2.** Functional parameters of aerobic capacity. (**A**) Maximal oxygen consumption rate (VO2peak) and maximal workload (**B**) measured in an incremental bicycle test before and after 6 weeks of aerobic exercise training and after 4 and 8 weeks of subsequent deconditioning in elderly and young men and women. Time to exhaustion (**C**), average VO<sup>2</sup> (**D**), average heart rate (**E**), and exercise economy (**F**) during an endurance test on bicycle at 80% of maximal workload in elderly and young men and women. *n* = 10 in young and *n* = 11 elderly. \* Significantly different (*p* < 0.05) from pretraining within age group. # Significantly different (*p* < 0.05) from 6 weeks of training within age group. §§§ Significantly different (*p* < 0.001) from young participants. All data are presented as means ± standard error (SE).

VO<sup>2</sup> (Figure 2D) and heart rate (Figure 2E) during the endurance test were overall ~30% lower in the elderly compared with the young individuals (*p* < 0.001). VO<sup>2</sup> (Figure 2D) and heart rate (Figure 2E) were ~15% decreased during the endurance test in both the elderly and the young subjects (*p* < 0.05) and remained so during 4 and 8 weeks of deconditioning. Exercise economy during the endurance test was improved by 12% and 10% in elderly and young individuals (*p* < 0.05), respectively, and remained improved after 4 weeks of deconditioning, but returned to pretraining levels after 8 weeks of deconditioning in both groups (Figure 2F). As a consequence of the relatively lower workload

compared with oxygen use during the endurance test in the elderly, exercise economy during the endurance test was overall ~30% lower in the elderly compared with the young individuals (*p* < 0.001) (Figure 2F).

#### *3.3. Mitochondrial Enzyme Activities*

At baseline, maximal muscle CS and mitochondrial electron transport chain complex I–IV activities did not differ between elderly and young individuals (Figure 3A–E). Six weeks of aerobic training increased muscle CS activity by 31% in elderly individuals (*p* < 0.05), which was the same as that observed in the young individuals (45%) (Figure 3A). Eight weeks of deconditioning decreased CS activity in the elderly individuals by 18% (*p* < 0.05), while CS activity remained at post-training level in young individuals (Figure 3A). The training-induced increases in complex I (163% and 152%; Figure 3B), II (63% and 58%; Figure 3C), III (63% and 49%; Figure 3D), and IV (51% and 40%; Figure 3E) activities were similar in elderly and young individuals. In elderly individuals, 8 weeks of deconditioning decreased complex I (Figure 3B), II (Figure 3C), III (Figure 3D), and IV activities (Figure 3E) by 40%, 8%, 25%, and 26% (*p* < 0.05), respectively, whereas only complex I (26%; Figure 3B) and II (9%; Figure 3C) activities decreased in young individuals after 8 weeks of deconditioning (*p* < 0.05). Interestingly, the change in enzyme activity with deconditioning significantly correlated with change in endurance capacity for complex I (*r* = 0.47, *p* < 0.05) and tended to correlate for complex III (*r* = 0.43, *p* = 0.05) and CS (*r* = 0.39, *p* = 0.09), whereas the change in enzymatic activity for complex II and IV was not significantly correlated to the change in endurance capacity with deconditioning. − −

**Figure 3.** Mitochondrial enzyme activities. Maximal enzyme activity of citrate synthase (CS; **A**), and mitochondrial complex I (**B**), II (**C**), III (**D**), and IV (**E**) in skeletal muscle pre and post six weeks of aerobic exercise training and after subsequent 8 weeks of deconditioning in young and elderly individuals. *n* = 10 in young group and *n* = 11 in the elderly group. \*/\*\*/\*\*\* *p* < 0.05/0.01/0.001, significantly different from pretraining within age group. #,## significantly different from 6 weeks of training within age group.

When correcting mitochondrial electron transport chain complex I–IV activities individually to CS activity, to take mitochondrial content into account, complex II (−26%) and III (−31%) activities were overall lower in the elderly compared with the young individuals pretraining and also after training and deconditioning (*p* < 0.05), whereas the CS-corrected complex I and IV activity was similar between young and elderly at all time points.

#### *3.4. Apoptosis Markers: Cleaved Caspase 3 and Bcl2*

There was no effect of aerobic training on cleaved caspase-3 protein content in either the elderly or the young individuals. Pretraining, elderly individuals had a 48% lower expression of cleaved caspase-3 protein content compared with young individuals (*p* < 0.05); however, after aerobic training and deconditioning, there was no longer any difference between the two groups (Figure 4A). Bcl2 protein expression decreased by 21% and 20% after aerobic training to a similar extent in the elderly and young individuals (*p* < 0.05), respectively; however, after 8 weeks of deconditioning, this was not different from pretraining levels in both groups (Figure 4B).

**Figure 4.** Apoptosis markers. Protein expression of cleaved caspase-3 (**A**) and B-cell lymphoma 2 (Bcl2) (**B**) in skeletal muscle pre and post 6 weeks of aerobic exercise training and after subsequent 8 weeks deconditioning period in young and elderly individuals. *n* = 10 in young group and *n* = 11 in the elderly group; however, due to lack of samples, only *n* = 6 in both groups in (**B**). (**C**) representative Western blots. Values are arbitrary units (means ± SE) and expressed relative to young group pretraining. § *p* < 0.05, young vs. elderly group within pretraining. \* *p* < 0.01, main effect of training compared to pretraining independently of age.

#### **4. Discussion**

Age-related loss of muscle mass and function may be related to changes in mitochondrial function with age and an impaired response to adapt to the physical activity level. However, only a few studies investigated age-related changes in mitochondrial function in response to aerobic training and deconditioning. In the present study, we investigated age-related changes of aerobic capacity, mitochondrial function, and apoptotic signaling markers with aerobic training and deconditioning and found that (1) only 6 weeks of aerobic training efficiently improved maximal aerobic capacity and mitochondrial function in the elderly individuals, (2) the training effect on aerobic capacity, endurance, mitochondrial enzyme activities, and apoptosis signaling markers in the elderly individuals was similar to that found in the young individuals despite an age difference of more than 50 years, and (3) with deconditioning, the training-induced increases in endurance and mitochondrial enzyme activities decreased in a faster manner in elderly compared with young individuals.

It was suggested that differences in aerobic capacity in elderly versus young healthy humans, at least in part, may be a result of differences in the ability to gain and maintain VO2peak with age [13,21,22]. However, in the present study, 6 weeks of intensive aerobic exercise training resulted in the same increase in VO2peak in elderly individuals compared with that found in young, gender-matched, sedentary individuals, indicating a similar ability to increase oxidative capacity in elderly vs. young individuals. Although the training period was longer than in the present (8–16 weeks), the effect on aerobic capacity was overall the same as previously observed [12–17]. The increase in VO2peak in the present study was found after only 6 weeks of aerobic training, suggesting that elderly individuals can increase oxidative capacity after a relatively short training period to the same extent as that seen in young healthy individuals.

Citrate synthase has been shown to be a strong marker of mitochondrial content. Thus, maximal CS activity strongly correlated with mitochondrial volume measured by electron microscopy in skeletal muscles of healthy, young men [41]. Moreover, maximal CS activity correlated with the improvement in mitochondrial volume after 6 weeks of aerobic training in skeletal muscle of young individuals [42]. In the literature, it has been debated whether there is an age-related decline in mitochondrial enzyme activities, since results from studies investigating this have been ambiguous. Several studies found decreased activity of CS and complex I–IV in muscle of elderly [15,43–47], indicating an age-related decline in mitochondrial content and function. Supporting this view, a study investigating the effect of age on mitochondrial content by transmission electron microscopy found a decrease in the content of mitochondria in elderly compared with young individuals [47]. In contrast, in the present study, CS and mitochondrial complex activities were similar at baseline between young and elderly, as we also recently showed between a similar cohort of young (~22 years) and elderly individuals (~82 years) [36] and in accordance with several other studies [13,48–50]. Interestingly, when mitochondrial complex activities were corrected relative to CS activity to take mitochondrial content into account, in the present study, complex II and III activities were lower in the elderly compared with the young individuals, implying a loss in the electron transport chain efficiency relative to mitochondrial content. It is possible that the mixed results from studies investigating the effect on age and mitochondrial function in part are related to differences in the pretraining level of physical activity in the investigated elderly individuals. Interestingly, in the present study, elderly individuals were able to increase CS activity (+31%) and mitochondrial complex activities (ranging between 61–163%) with training that matched that found in the healthy young individuals, which emphasizes that the ability to respond to an increase in demand in muscle enzymes in tricarboxylic acid (TCA) cycle and oxidative phosphorylation is preserved at least to the eighth decade of life. The few studies that investigated CS and/or mitochondrial complex activities in elderly of 60–80 years of age did not compare results to young but found a similar increase after 12–16 weeks of training [13,15,16,43], suggesting a similar ability of elderly of 60 and 80 years of age to respond to aerobic training. A recent study with only 6 weeks of high-intensity exercise training also showed improved CS activity and mitochondrial complex protein contents in "younger" elderly (63 years old) men and women [12], which, together with the intense protocol in the present study, underscores that mitochondria can adapt to even short-term training interventions in elderly of both 60 and 80 years of age, when the intensity and frequency of the training are high.

In addition to the exercise training intervention, we included a subsequent deconditioning period to evaluate mitochondrial dynamics in aged human skeletal muscle, which, to our knowledge, has not been studied previously in elderly healthy individuals. Deconditioning after exercise training was investigated in a few studies in healthy young individuals, and data implied that oxidative capacity, muscle mitochondrial protein content, and enzyme activities return to pretraining levels after 6–8 weeks in young individuals [23–27]. In the present study, mitochondrial content judged by CS and mitochondrial complex activities returned to pretraining levels after 8 weeks of deconditioning in the elderly, which was not seen in the young healthy individuals. Thus, enzyme activity of CS and complex I, III, and IV decreased in the elderly to a larger extent than in the young individuals. This indicates that the turnover rate of mitochondrial enzymes in the TCA cycle, as well as the oxidative

phosphorylation, is fast and even more rapid in skeletal muscle of elderly. Thus, it seems as the ability to obtain oxidative capacity and increase mitochondrial volume with intensive aerobic training is preserved with age, but is lost faster in aged than in young muscle during subsequent deconditioning. A sedentary lifestyle in elderly individuals may, therefore, be even more deleterious to muscle health than in young individuals.

Endurance capacity is essential in order to maintain independence, reduce incidence of disability, and sustain a high quality of life in older people. In the present study, we found that 6 weeks of intensive aerobic exercise resulted in a remarkable increase in the time to exhaustion during an endurance test in the elderly individuals by 2.4-fold. Moreover, this training-induced increase in endurance was likely, at least in part, mediated by an improved exercise economy, reflecting the capacity to turn oxygen consumption into mechanical work and, hence, lower usage of VO<sup>2</sup> at the given power. This finding suggests a functional relevance of the training-induced increase in muscle mitochondrial respiratory enzyme activities, through an improved ability to sustain a high energy-production and also a more energy-efficient power production over a longer period of time. The present study is, to our knowledge, the first to demonstrate that the effect on aerobic capacity and muscle mitochondrial function and efficiency seemingly translates into functional improvement of endurance and exercise economy in elderly. In this line, it should be mechanistically studied in future investigations whether aerobic exercise training prevents sarcopenia by improving mitochondrial function and dynamics [51]. Interestingly, with deconditioning, a faster decrease in endurance capacity was observed among elderly compared with young individuals in accordance with similar decreases in CS and mitochondrial complex activities, indicating that, although elderly individuals improve endurance with training in the same manner as young individuals, aerobic endurance seems to be lost faster in elderly individuals, likely related to enhanced degradation of muscle mitochondrial enzymes. To support this notion, we found, despite the modest number of participants in the present study, that the loss of enzyme activity of CS and complex I and III in response to deconditioning tended to correlate to the reduction in endurance capacity. Of note, the faster decline in mitochondrial enzyme activity with deconditioning was in the present study observed in elderly of ~80 years of age, and it remains to be clarified whether 60–75-year-old individuals that are often investigated in the scientific literature would be more affected by deconditioning compared with young individuals. Importantly, a faster decline in endurance performance during deconditioning contrasts with the loss of strength performance after 6 weeks of resistance training, which we recently showed to be similar between young and elderly individuals (~82 years) after comparable 8 weeks of deconditioning [36].

Even though some studies in rodents indicated that apoptosis may play a role during muscle senescence [32], the involvement of age-related apoptosis of skeletal muscle and its regulation with training and deconditioning is poorly understood. Caspase-3 plays an important role in mediating cell death, and Bcl2 is thought to be an antiapoptotic driver. Interestingly, we found a lower muscle content of active caspase-3 (cleaved caspase-3) and a similar Bcl2 expression in the elderly compared with young individuals at baseline. This indicates, at least in healthy elderly individuals, that markers of the muscle intrinsic apoptotic pathway are not upregulated. These findings contrast with findings in rodents, in which increased apoptosis in old muscle of rodents was suggested on the basis of findings of an increased expression of proapoptotic marker cleaved caspase-3 protein [31] and a lower expression of the antiapoptotic Bcl2 protein [28–30]. Moreover, in the present study, caspase-3 activity remained similar in elderly and young skeletal muscle after 6 weeks of aerobic training, indicating that exercise training does not induce a higher apoptosis activity. In contrast, Bcl2 protein content decreased slightly in response to training to the same extent in young and elderly, implying either less antiapoptotic signaling after training independently of age or that Blc2 content is not directly coupled to apoptosis rate. To our knowledge, this study is the first to investigate apoptotic markers with training and deconditioning in human muscle of elderly compared with young individuals. Although we only investigated a few markers of a complex signaling, the present results do not substantiate the hypothesis that increased apoptosis with time is the mediator of age-related muscle

mass. The faster decline with deconditioning in endurance capacity and mitochondrial enzyme activity could relate to an age-related decline in mitochondrial fusion/fission regulation or an impaired matching of lysosomal mitophagy flux to the demand in aged muscle during deconditioning [51]. In support of the latter, we previously showed in young individuals that 3 weeks of one-legged aerobic training improved the capacity for autophagosomal formation [40], which is also found to occur in elderly [52], emphasizing the importance of physical activity to improve or maintain lysosomal mitophagic capacity. From studies in rodents [53–55] and humans [52], it is known that both muscle disuse and aging are associated with impaired mitophagy regulation, and it is, hence, likely that impaired mitophagy and mitochondrial function with deconditioning contribute to accelerated impairment in elderly, which should be addressed in future studies. Overall, accelerated decline in mitochondrial function and sarcopenia seems not to be driven by increased muscle apoptosis in human muscle, and further investigations are needed to elucidate the responsible molecular mechanisms driving sarcopenia and age-related inactivity-induced mitochondrial impairments.

The present study had some limitations that must be acknowledged. It was suggested that potential sex-specific adaptations to aerobic training exist [12]. We recognize that the present study included both men and women but that the number of participants was not optimal to detect an intervention × sex interaction; however, the present study was primarily designed to investigate the effects of training and deconditioning in elderly vs. young individuals. Studies with more subjects are warranted to evaluate potential sex-specific age-related adaptations to training and deconditioning.

#### **5. Conclusions**

In the present study, we found that 6 weeks of aerobic training efficiently improved maximal aerobic capacity and mitochondrial function in elderly individuals to the seemingly same extent as in young individuals despite an age difference of more than 50 years. This implies that aerobic exercise training is a potent tool to combat age-related loss of aerobic capacity and mitochondrial function. However, with deconditioning, we present the novel finding that the training-induced increases in performance and mitochondrial enzyme activities seemingly decreased in a faster manner in elderly compared with young individuals. This accelerated loss of mitochondrial function in the elderly with deconditioning could play a role in the development of mitochondrial dysfunction and sarcopenia during aging, and responsible mechanisms need to be investigated further in future studies.

**Author Contributions:** Conceptualization, S.P.A. and T.D.J.; methodology, S.P.A., F.D.T., T.K., and T.D.J.; investigation, A.M.F., S.P.A., K.A.N.Q., F.D.T., T.K., M.C.Ø., and T.D.J.; resources, T.K., J.V. and T.D.J.; data curation, A.M.F., S.P.A., K.A.N.Q., T.D.K.; writing—original draft preparation, A.M.F., K.A.N.Q., T.D.J.; writing—review and editing, A.M.F., S.P.A., K.A.N.Q., F.D.T., T.K., M.C.Ø., J.V. and T.D.J.; visualization, A.M.F.; supervision, T.K., J.V. and T.D.J.; project administration, S.P.A. and T.D.J.; funding acquisition, J.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** A.M.F. was supported by a research grant from the Danish Diabetes Academy (grant number NNF17SA0031406), which was funded by the Novo Nordisk Foundation. A.M.F. was further supported by the Alfred Benzon Foundation.

**Acknowledgments:** We thank Tessa Munkeboe Hornsyld and Danuta Goralska-Olsen at the Copenhagen Neuromuscular Center, University of Copenhagen, Denmark for excellent technical assistance. Lastly, we would like to gratefully recognize the volunteers for participating in this invasive and demanding study.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake**

**Ilse J. M. Hagedoorn 1,\*, Niala den Braber 1,2 , Milou M. Oosterwijk <sup>1</sup> , Christina M. Gant 3,4 , Gerjan Navis <sup>3</sup> , Miriam M. R. Vollenbroek-Hutten 1,2, Bert-Jan F. van Beijnum <sup>2</sup> , Stephan J. L. Bakker <sup>3</sup> and Gozewijn D. Laverman <sup>1</sup>**


Received: 21 August 2020; Accepted: 23 September 2020; Published: 25 September 2020

**Abstract:** Objective: In order to promote physical activity (PA) in patients with complicated type 2 diabetes, a better understanding of daily movement is required. We (1) objectively assessed PA in patients with type 2 diabetes, and (2) studied the association between muscle mass, dietary protein intake, and PA. Methods*:* We performed cross-sectional analyses in all patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT) between November 2016 and November 2018. Patients were divided into four groups: <5000, 5000–6999, 7000–9999, ≥ 10,000 steps/day. We studied the association between muscle mass (24 h urinary creatinine excretion rate, CER) and protein intake (by Maroni formula), and the main outcome variable PA (steps/day, Fitbit Flex device) using multivariate linear regression analyses. Results: In the 217 included patients, the median steps/day were 6118 (4115–8638). Of these patients, 48 patients (22%) took 7000–9999 steps/day, 37 patients (17%) took ≥ 10,000 steps/day, and 78 patients (36%) took <5000 steps/day. Patients with <5000 steps/day had, in comparison to patients who took ≥10,000 steps/day, a higher body mass index (BMI) (33 ± 6 vs. 30 <sup>±</sup> 5 kg/m<sup>2</sup> , *p* = 0.009), lower CER (11.7 ± 4.8 vs. 14.8 ± 3.8 mmol/24 h, *p* = 0.001), and lower protein intake (0.84 ± 0.29 vs. 1.08 ± 0.22 g/kg/day, *p* < 0.001). Both creatinine excretion (β = 0.26, *p* < 0.001) and dietary protein intake (β = 0.31, *p* < 0.001) were strongly associated with PA, which remained unchanged after adjustment for potential confounders. Conclusions: Prevalent insufficient protein intake and low muscle mass co-exist in obese patients with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and physical activity in increasing or maintaining muscle mass in patients with type 2 diabetes.

**Keywords:** type 2 diabetes; physical activity; muscle mass; protein intake; accelerometer

#### **1. Introduction**

Type 2 diabetes is a predominately lifestyle-related disease and has become one of the major global public health concerns, with highest prevalence in older adults [1]. Sufficient physical activity (PA) is a main focus of treatment, in addition to improving diet quality. There are two different aspects

of PA: aerobic training and resistance exercise. While guidelines first mainly recommended moderate to vigorous PA, contemporary public health guidelines state that 'some physical activity is better than none' by suggest reducing the time spent in sedentary behaviour [2]. Total steps per day is a good indicator of the overall volume of physical activity [3].

However, the vast majority of patients with type 2 diabetes do not adhere to the American Diabetes Association (ADA) guidelines of >150 min per week of moderate to vigorous PA, which is comparable with 7000 steps per day [3–5]. Traditionally, a goal of 10,000 steps per day has been advocated by popular media, although this goal is under debate in scientific literature [6,7]. In order to promote PA and reduce sedentary behaviour, a better understanding of total daily movement is required, especially in patients with complicated type 2 diabetes.

In regard to PA, sufficient muscle mass is mandatory to perform PA, and conversely, PA promotes an increase in muscle mass. Compared with non-diabetic subjects, patients with type 2 diabetes show decreased muscle strength and mass [8,9]. In type 2 diabetes, reduced muscle mass and muscle function, defined as sarcopenia, have been implicated both as a cause and as a consequence of increased insulin resistance [8–10]. Furthermore, it is known that low muscle mass in obese individuals is associated with frailty, disability, and increased morbidity and mortality [11].

However, dietary counselling (such as is performed in the geriatric population) consists mainly of caloric restriction, and not the preservation of muscle mass. Adequate protein intake is an important requirement for sustaining, and especially increasing, muscle mass, which has been confirmed by several observational and intervention studies [12–17]. Moreover, combining physical exercise with protein intake has a positive synergistic effect on muscle protein synthesis [16,17]. Therefore, adequate protein intake might be a current blind spot in the treatment of type 2 diabetes.

We hypothesize that in patients with complicated type 2 diabetes, low protein intake and low muscle mass are associated with low PA, and the former could be an important actionable item to improve PA. Therefore, here we (1) objectively measure PA (in steps/day) in patients with complicated type 2 diabetes, and (2) investigate the association between protein intake and muscle mass and PA.

#### **2. Materials and Methods**

#### *2.1. Patient Inclusion*

This study was performed in the DIAbetes and LifEstyle Cohort Twente (DIALECT), an observational cohort study in patients with complicated type 2 diabetes mellitus, treated in the secondary healthcare level in the outpatient clinic of the Ziekenhuisgroep Twente (ZGT), Almelo and Hengelo, the Netherlands. The study consists of two sub-cohorts: DIALECT-1 and DIALECT-2. The general procedures have been described extensively previously [18]. In DIALECT-2, the data collection at baseline is more extensive, including a one-week PA registration.

The study was performed in accordance with the Helsinki agreement and the guidelines of good clinical practice, has been approved by the local institutional review boards (METC-registration numbers NL57219.044.16 and 1009.68020) and is registered in the Netherlands Trial Register (NTR trial code 5855). Prior to participation, all patients signed an informed consent form. All adult patients with type 2 diabetes treated in the secondary healthcare level in the outpatient clinic of internal medicine in ZGT Hospital were eligible for participation. The patients were treated in the secondary healthcare level because the diabetes care became complex for primary healthcare services (for example, in the presence of complications such as nephropathy or because of a complex insulin schedule). Exclusion criteria were renal replacement therapy, inability to understand the informed consent procedure, and inability to walk. We report here on all patients included in DIALECT-2 between November 2016 and November 2018.

#### *2.2. Data Collection*

Participation in DIALECT-2 consisted of at least two hospital visits with one week in between. Information on medical condition and medication was obtained from electronic patient files and verified

with the patient during the baseline visit. Smoking habits were collected through questionnaires. Anthropometric measurements, leg length, and presence of diabetic polyneuropathy were obtained from physical examination at baseline. Leg length was measured using a tape measure from the anterior superior iliac spine to the ground. Polyneuropathy was assessed by touch test (Semmes Weinstein monofilament) and vibration (Vibratip) by the on–off method; both tests have been validated as screening methods for polyneuropathy [19]. Polyneuropathy was present if at least one of the two tests was positive. Body composition parameters were determined by Bio impedance using a TANITA device (type BC-418MA, Tokyo, Japan), which calculates segmental body composition, including fat percentage and predicted muscle mass. Blood samples were taken from a single non-fasting venapunction, and patients collected 24 h urine to provide objective data on nutritional intake, including protein intake. We used the 24 h urinary creatinine excretion rate (CER) as a measure of muscle mass [11,20,21]. The estimated daily protein intake (g/kg/day) was calculated using the universally adopted formula of Maroni, ((24 h urea excretion × 0.18) + 15 + 24 h protein excretion)/weight (kg) [22]. Blood pressure was measured in supine position by an automated device for 15 min with one-minute intervals (Dinamap®; GE Medical systems, Milwaukee, WI, USA). The mean systolic and diastolic pressure of the last three measurements was used for further analysis.

#### *2.3. Main Outcome: Physical Activity*

During 8 consecutive days, daily movement was measured by a triaxial Fitbit accelerometer worn around the wrist on the non-dominant side. The devices used were either a Fitbit Flex (Fitbit Inc., Boston, MA, USA), a Fitbit charge HR (Fitbit, San Francisco, CA, USA), or Fitbit Charge 2 (Fitbit Inc., San Francisco, CA, USA). These Fitbit devices share the same recording mechanisms and record the number of steps taken on a minute-to-minute basis. Patients were asked to adhere to their daily activities as normal and were blinded from the online activity data. Also, the Fitbit screens showed no results. Only during swimming or showering was the Fitbit removed. At visit 2 (day 8), the patients returned the Fitbit and data were transferred to a hospital server for further analysis. Patients were asked to write down information regarding non-wearing time in a lifestyle diary. Valid days were defined as days without significant non-wearing time (i.e., >2 h non-wearing time during waking hours). Patients with more than two days of significant non-wearing time were excluded. To indicate the total daily movement, we used the average of the total steps per day, excluding day 1 and 8 from the average because of non-wearing time.

#### *2.4. Statistical Analysis*

Statistical procedures were performed by using SPSS statistics (IBM Statistics for Windows, Version 23.0, Armonk, NY, USA). Normality of data was determined by visual inspection of histograms. Data were presented as mean ± standard deviation (normal distribution), as median and interquartile range (IQR 25th–75th percentiles, skewed data), or as number and percentage (dichotomous and categorical data). To compare the characteristics of total steps per day, the population was divided into four different groups based on reference values from current literature (i.e., <5000, 5000–6999, 7000–9999, ≥10,000 steps per day) [3]. Differences between the groups were analysed using One-Way ANOVA, Kruskal–Wallis, or Chi-square test when appropriate. A two-sided *p* < 0.05 was considered statistically significant. The estimated daily protein intake was divided into three groups (i.e., <0.8 g/kg/day, 0.8–1.2 g/kg/day, and >1.2 g/kg/day). The recommended dietary protein intake is ≥0.8 g/kg/day [12,23].

To investigate whether 24 h CER and protein intake were associated with total steps/day, we performed multivariate linear regression analyses. First, we identified possible confounders using univariate analyses. Model 2, adjusted for age and gender, was the main basis for confounder selection. Parameters with a *p* < 0.15 were considered contenders for the multivariate model. For each group of closely associated variables (for example, body mass index (BMI), waist circumference, and hip circumference as measures of body size), we included the variable with the highest β for the multivariate model. Potential interaction of protein intake and CER with total steps/day was evaluated

by inclusion of the product term in the linear regression analysis. We considered a *p* < 0.10 to be statistically significant for the product term. To graphically represent the interaction between protein intake, CER, and total steps per day, we created nine groups based on the tertiles of protein intake and tertiles of muscle mass. Low, medium, and high represent respectively the lowest, middle, and highest tertiles of protein intake and muscle mass.

#### **3. Results**

#### *3.1. Baseline Characteristics and Total Steps per Day*

Of 231 eligible participants, 217 patients were included in the study. The reasons for exclusion were: hardware malfunction (*n* = 6), non-fitting wristband (*n* = 4), patient dropped out during participation (*n* = 2), and patient not able to walk (*n* = 2) (Figure S1). Patient characteristics stratified by total steps per day are shown in Table 1.

Median total steps per day was 6118 (4115–8638, data not shown). Of the total study population, 85 patients (39%) took ≥7000 steps/day, of whom 37 patients (17%) reached ≥10,000 steps/day (Table 1).

The mean age of the total study population was 65 ± 12 years, two-thirds were men, and the mean BMI was 32 <sup>±</sup> 6 kg/m<sup>2</sup> . Of all patients, 64% used insulin, and the mean HbA1c was 60 ± 13 mmol/mol (7.6% ± 3.3%). The prevalence of micro- (74%) and macrovascular (35%) complications was high. Compliance with wearing of the Fitbit sensor was good; 22 patients reported significant non-wearing time (>2 h/day) at any day during day 2 until day 7, however, no patient had more than two days of non-wearing time (compliance data not shown).

The mean age was highest (69 ± 11 years) in the group of patients with <5000 steps per day (*p* < 0.001). There were no differences in gender between the groups (*p* = 0.99). Patients with <sup>&</sup>lt;5000 steps/day had the highest BMI (33 <sup>±</sup> 6 kg/m<sup>2</sup> , *p* = 0.009) and the highest waist- and hip circumference (waist: 116 ± 14 cm, *p* = 0.001; hip: 115 ± 14 cm, *p* = 0.009). Both measurements of muscle mass (i.e., 24 h CER and percentage of predicted muscle mass (PMM) using bio-impedance) were lowest in patients with 5000 steps/day (*p* = 0.001 and *p* = 0.06, respectively).

No significant differences were observed in HbA1c, insulin use, and years of diabetes between the groups. Patients with <5000 steps per day had the most pack-years of smoking (*p* = 0.005), the lowest diastolic blood pressure (0.02), and the lowest HDL-cholesterol (*p* = 0.03). The prevalence of micro- and macrovascular complications was consistently and progressively lower in each group of increasing number of steps/day, especially for diabetic kidney disease (*p* = 0.004), polyneuropathy (*p* = 0.008), and cerebrovascular disease (*p* = 0.008). Protein intake was also lowest in patients with <5000 steps/day (0.84 g/kg/day, *p* < 0.001, Figure 1). Almost half of all patients with <5000 steps per day had a protein intake <0.8 g/kg/day.



**Table 1.** Patient characteristics stratified by total steps per day.

a

3; High ISCED 4–8: c

interquartile

 range (IQR 25th–75th),

Significant

 difference

 from

Predicted

 Muscle Mass %: TANITA predicted

 or in number and

<5000 steps/day.

Education

 level according

 to the

 muscle mass (kg) divided by total body weight (kg). Data presented

(percentage).

 eGFR: estimated

 glomerular

 filtration rate. TIA: transient ischemic attack.

International

 Standard

Classification

 of Education

 (ISCED), as follows: Low: ISCED 1–2; Medium:

 as mean ±

standard

 deviation,

 as median and

 ISCED

**Figure 1.** Protein intake, body mass index (BMI), and 24 h urinary creatinine excretion according to total steps per day. Distribution of total protein intake (**A**) and urinary creatinine excretion and body mass index (**B**) in four groups of total steps per day. (**A**) demonstrates that insufficient protein intake is significantly more prevalent in patients with <5000 steps/day. (**B**) shows higher body mass index and lower creatinine excretion in patients with <5000 steps/day, demonstrating a more unfavourable body composition.

#### *3.2. Association between Urinary Creatinine Excretion, Total Protein Intake, and Total Steps per Day*

To analyse the association between total steps per day, muscle mass (24 h CER), and daily dietary protein intake, we performed linear regression analyses. Unadjusted, both CER (β = 0.28, *p* = 0.03) and dietary protein intake (β = 0.29, *p* = 0.004) (Model 1) were positively associated with steps/day. When adjusting for possible confounders (Table S1), both for CER and protein intake, the association with total steps/day did not markedly change (Table 2). It should be noted that the predicted variance of both models remained low (0.23 and 0.24, respectively). There was a significant interaction between CER and protein intake on total steps per day, where higher CER combined with higher protein was associated with more steps/day (*p* = 0.096, Figure 2). As there was a very strong correlation between CER and dietary protein intake (*R* = 0.57), both variables could not be inserted simultaneously in the analysis.


**Table 2.** Multivariate linear regression analyses on the associations between CER, protein intake and total steps/day (dependent variable)

CER: creatinine excretion rate. Model 1 is unadjusted; Model 2 is adjusted for model 1 and age and gender; Model 3 is adjusted for model 2 and BMI and leg length; Model 4 is adjusted for model 3 and pack-years; Model 5 is adjusted for model 4 and eGFR < 60 mL/min/1.73 m<sup>2</sup> , polyneuropathy, and presence of macrovascular disease.

**Figure 2.** Low, medium, and high represent the lowest, middle, and highest tertiles of protein intake and creatinine excretion. The figure shows the interaction between urinary creatinine excretion (CER) and protein intake on total steps per day. Both high CER and high protein intake were associated with more steps/day, and total steps per day was highest in those with both high CER and high protein intake.

#### **4. Discussion**

≥ We investigated the total daily physical activity (PA) of patients with complicated type 2 diabetes. We found that more than one-third of the study participants had limited activity (less than 5000 steps per day). On the other hand, 39% of participants took ≥7000 steps per day, which has been advocated as the movement target for adults ≥ 65 years and/or patients with chronic diseases [3], demonstrating that sufficient PA in a complicated type 2 diabetes population is indeed a reachable goal.

≥ Our main finding was that low muscle mass was an important determinant of low PA. Additionally, protein intake was significantly and relevantly lower in patients with both low PA and low muscle mass. It is tempting to speculate on a downward spiral of reduced protein intake, lower muscle mass, and reduced PA, against the background of a sedentary lifestyle. The insight that insufficient protein intake is associated with low muscle mass and physical inactivity may provide an important actionable item to improve physical fitness in patients with type 2 diabetes: namely, increase protein intake.

Low muscle mass is increasingly recognized as an important health concern in patients with chronic disease, diminishing physical fitness and PA. In contrast to previous beliefs, declining muscle mass is not only due to ageing and physical inactivity, but has many other contributing causes, such as mitochondrial dysfunction [11,24,25]. This is especially important in patients with type 2 diabetes, as data suggest skeletal muscle lipid content is associated with systemic insulin resistance [11]. Damage to the skeletal muscles, with pronounced and accelerated decline in muscle quality, has been described as a new complication of diabetic patients attributed to their longer survival [8]. Insulin resistance and oxidative stress are components of the pathophysiological basis of sarcopenia, which would be related to characteristic components of diabetes, such as vascular alterations, chronic inflammation, and lipid infiltration in muscles [8,11]. In regard to our population, 24 h CER in the group with ≤5000 steps per day (11.7 ± 4.8 mmol/24 h) was significantly lower compared to the

total study population (13.2 ± 5 mmol/24 h), and also lower when compared to the general Dutch population (13.3 ± 4.1 mmol/24 h, based on data from the Lifelines cohort study) [12]. However, it should be noted that no diagnostic methods or definitive cut-off points exist to identify patients who might benefit from muscle-boosting therapy.

Adequate protein intake is an important requirement for sustaining, and especially increasing, muscle mass, which has been confirmed by several observational and intervention studies [12–17]. Moreover, combining physical exercise with protein intake has a positive synergistic effect on muscle protein synthesis [16,17].

The recommended dietary allowance (RDA) and the Netherlands Nutrition Centre [12,23] recommend a dietary protein intake of ≥0.8 g/kg/day. However, for elderly adults, the Dutch guideline suggests a higher protein intake (1.2–2.0 g/kg/day) to maintain optimal muscle health [26,27]. We found that almost half of all patients (46%) in the group of <5000 steps per day had a daily protein intake < 0.8 g/kg/day, and only 12% had an intake of >1.2 g/kg/day. To our knowledge, this is the first study in patients with type 2 diabetes that has highlighted the insufficient protein intake of inactive patients with type 2 diabetes. However, BMI and waist circumference were higher in patients with low PA, consistent with altered body composition in inactive patients. This is in line with previous studies in patients with type 2 diabetes [4,28,29]. Low muscle mass and function have strong negative prognostic impacts in obese individuals, which may lead to frailty disability and increased morbidity and mortality [11]. However, awareness of the importance of muscle maintenance in obesity is low among clinicians and scientists [11]. The European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the study of Obesity (EASO) recognize and identify obesity with altered body composition due to low skeletal muscle function and mass as a scientific and clinical priority for researchers and clinicians. ESPEN and EASO therefore call for action in particular regard to optimal nutritional therapy. Generally, the first step in treating obese patients with type 2 diabetes is weight loss interventions by following a caloric restricted diet, which, however, might increase the risk for undesirable decreases in muscle mass.

To our knowledge, this is the first study to objectively measure daily PA by using steps/day in complicated type 2 diabetes. Most of the previous studies in type 2 diabetes used metabolic equivalent (MET) or counts per minute (CPM) to measure daily movement, which makes it somewhat difficult to compare previous results with our findings [4,24,25,28–34]. However, in a study population with older patients (≥55 years) with type 2 diabetes, the average total steps per day was similar to our results [34]. In contrast to this previous study, which showed that older women had fewer steps per day, we found no difference in steps/day between genders.

Additionally, we found that the presence of micro- and macrovascular complications was higher in patients with physical inactivity. This is in line with a recent review on diabetic polyneuropathy and nephropathy [35]. Interestingly, diabetic polyneuropathy is associated with lower muscle strength measured by knee extension force [25,32,35], providing an alternative cause of muscle mass decline in addition to reduced dietary protein intake. Additionally, in patients with chronic kidney disease, uremic muscle mass decline has been suggested by a significant inverse association between uremic toxin indoxyl sulphate and skeletal muscle mass [33,35]. Of note, in our study, a third of the patients with ≥10,000 steps per day had polyneuropathy and nephropathy (28% and 33%, respectively), suggesting that sufficient PA is indeed possible in spite of the presence of these complications. However, in contrast to other studies in patients with type 2 diabetes, we found associations between HDL-cholesterol, diastolic blood pressure, macrovascular complications, and physical activity [4,28,29].

Strengths of our study included the objective measurements of daily movement by the Fitbit Flex, a light and simple wristband, well applicable in daily life clinical practice that hardly interferes with daily activities. We chose to present steps/day, which is easily interpretable by clinicians and patients. Another strength of our study was muscle mass estimation by 24 h CER, which is well accepted for estimation of total body skeletal muscle mass, even in patients with advanced renal failure [12,21]. Additionally, we objectively determined protein intake by 24 h urinary urea excretion. In the future, we plan to extend our analysis to also include muscle quality using gait speed, as well as quality of life questionnaires. An important limitation of our study is the cross-sectional design, which allows only research of associations and not causality. Additional prospective studies are warranted to confirm our findings. Another limitation is that one-week record of the Fitbit may not be sufficiently representative of PA, as certain activities, such as swimming, and seasonal variations were not taken into account. However, only 8 patients of the total 217 patients (4%) recorded swimming in their lifestyle diary. Secondly, we had the sampling periods of our population distributed over the seasons. Making these effect negligible.

Our study has important clinical implications. We found clear associations between low protein intake, loss of muscle mass, and low PA in patients with complicated type 2 diabetes. Our study suggests that optimizing protein intake might be a first step to improving physical fitness in patients with type 2 diabetes. As current dietary guidelines focus on reducing overall caloric intake, and carbohydrate intake in particular, adequate protein intake might be an important blind spot in current nutritional management. This has also been advocated in previous studies, which suggest that dietary protein should be prescribed together with physical exercise in order to optimize muscle health [12,16,17,36]. The review by Scot and colleagues also emphasizes that lifestyle modification programs for older adults with type 2 diabetes, particularly for those with sarcopenia, should incorporate progressive resistance training, along with adequate intakes of protein and vitamin D, which may improve both functional and metabolic health and prevent undesirable decreases in muscle mass associated with weight loss intervention [9]. In the future, we want to include data from the Food Frequency Questionnaire (FFQ) in the analyses in order to investigate how intakes of total energy, carbohydrate, fat, and vitamin D may contribute to muscle mass and physical activity. It is important to note that the source of dietary protein (animal or vegetable) should also be taken into account, as we have previously shown that higher vegetable protein intake is associated with lower prevalence of renal function impairment [37].

#### **5. Conclusions**

In conclusion, our study shows that prevalent low protein intake and low muscle mass co-exist in patients with complicated type 2 diabetes with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and PA in increasing or maintaining muscle mass in patients with type 2 diabetes.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/10/3104/s1, Figure S1: flow chart of patient inclusion, Table S1: linear regression analyses for total steps per day.

**Author Contributions:** I.J.M.H. researched data and wrote the manuscript. N.d.B. analyzed the Fitbit data and reviewed/edited the manuscript. C.M.G., G.D.L., G.N., S.J.L.B. and M.M.R.V.-H. researched data and reviewed/edited the manuscript. M.M.O. and B.-J.F.v.B. reviewed/edited the manuscript. G.D.L. is the principal investigator of DIALECT and the guarantor. All authors have read and agreed to the published version of the manuscript.

**Funding:** Funding was provided from the ZGT hospital research fund.

**Acknowledgments:** The authors would like to thank Nicole Oosterom, Annis Jalving, Roos Nijboer, and all of the students who have participated in DIALECT 1 and 2, Ziekenhuisgroep Twente, for their general contributions to DIALECT, including patient inclusion.

**Conflicts of Interest:** The authors report no potential conflicts of interest relevant to this article.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **Respiratory Muscle Strengths and Their Association with Lean Mass and Handgrip Strengths in Older Institutionalized Individuals**

**Francisco Miguel Martínez-Arnau 1,2 , Cristina Buigues 2,3, Rosa Fonfría-Vivas 2,3 and Omar Cauli 2,3,\***


Received: 15 July 2020; Accepted: 19 August 2020; Published: 24 August 2020

**Abstract:** The study of reduced respiratory muscle strengths in relation to the loss of muscular function associated with ageing is of great interest in the study of sarcopenia in older institutionalized individuals. The present study assesses the association between respiratory muscle parameters and skeletal mass content and strength, and analyzes associations with blood cell counts and biochemical parameters related to protein, lipid, glucose and ion profiles. A multicenter cross-sectional study was performed among patients institutionalized in nursing homes. The respiratory muscle function was evaluated by peak expiratory flow, maximal respiratory pressures and spirometry parameters, and skeletal mass function and lean mass content with handgrip strength, walking speed and bioimpedance, respectively. The prevalence of reduced respiratory muscle strength in the sample ranged from 37.9% to 80.7%. Peak expiratory flow significantly (*p* < 0.05) correlated to handgrip strength and gait speed, as well as maximal inspiratory pressure (*p* < 0.01). Maximal expiratory pressure significantly (*p* < 0.01) correlated to handgrip strength. No correlation was obtained with muscle mass in any of parameters related to reduced respiratory muscle strength. The most significant associations within the blood biochemical parameters were observed for some protein and lipid biomarkers e.g., glutamate-oxaloacetate transaminase (GOT), urea, triglycerides and cholesterol. Respiratory function muscle parameters, peak expiratory flow and maximal respiratory pressures were correlated with reduced strength and functional impairment but not with lean mass content. We identified for the first time a relationship between peak expiratory flow (PEF) values and GOT and urea concentrations in blood which deserves future investigations in order to manage these parameters as a possible biomarkers of reduced respiratory muscle strength.

**Keywords:** spirometry; urea; fatigue; respiratory system; skeletal muscles; lipids; transaminases

#### **1. Introduction**

Sarcopenia is a geriatric syndrome that according to the European Working Group on Sarcopenia in Older People (EWGSOP) guidelines, is defined as a progressive and generalized loss of skeletal muscle mass and strength, with a risk of adverse outcomes, such as functional capacity impairment, dependence, falls and fractures, negative impact on quality of life, hospitalization and death [1]. In older individuals, sarcopenia has a widespread effect on all skeletal muscles throughout the body, but the features of sarcopenia in the respiratory muscles and its relationship with established sarcopenia parameters such as reduced lean mass, poor muscular strength and functional impairment [1,2] have been less widely investigated in older individuals [3,4], and no studies have been performed in nursing

home residents, a significant population in western societies with a huge burden of comorbidities, including sarcopenia [5–8]. Besides the loss of muscular mass and strength, aging leads to proteolysis of elastic fiber and an increase in collagen in the pulmonary parenchyma, which coupled with an increase in the rigidity of the chest wall generates a mechanical disadvantage, and weakness of the respiratory muscles over time [9,10]. These changes results in a diminished respiratory muscle strength (RMS), referred to as sarcopenia of the respiratory muscle or reduced respiratory muscle strength as just it is analysed by quantifying the decline in respiratory function [3]. Respiratory muscles are also responsible of producing a proper pressure difference between inspiration and expiration to generate a correct airway flow rate, which guarantees a good respiratory function [11]. Other respiratory parameters, such as vital capacity (VC), forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and peak expiratory flow rate (PEF) are also affected as a result of changes in elastic recoil and thorax compliance associated with aging [3,11,12]. RMS is therefore related to FEV1, FVC, and PEF. Even in patients without airway obstruction, these functions may decline due to age-induced weakness of the respiratory muscles. PEF measurements were recommended over RMS measurements for the assessment of respiratory function in the EWGSOP consensus report published in 2010 [2]. However, the EWGSOP report also indicated that PEF measurements should be used in association with other assessments, because there is a limited evidence about the relationship between PEF and skeletal muscle mass/sarcopenia in older adults. A previous study revealed that PEF is a significant predictor of mortality in older adults [13,14]. Further studies have demonstrated that sarcopenia is related to an increased incidence of pulmonary complications after surgery [15–17] and aspiration pneumonia mortality [18]. Izawa et al. [19] evaluated the relationship between maximal inspiratory pressure (MIP) and physical function as a measure of sarcopenia in older patients with heart disease, and found that sarcopenic patients presented lower values of MIP which also correlated with reduced skeletal muscle mass index, gait speed and hand grip strength. There is a lack of studies demonstrating the association between respiratory muscle weakness and sarcopenia parameters (reduced lean mass and muscular strength and low physical performance) in older institutionalized individuals. Moreover, no studies about the relationship of respiratory muscle function and blood analytical parameters in sarcopenic individuals have been performed. The objectives in this study were therefore to compare respiratory muscle function with lean mass content, handgrip strength and functional impairment (walking speed) in order to assess whether there is an association between respiratory muscle parameters such as the maximum respiratory pressures and peak expiratory flow and parameters of skeletal muscular function. Since skeletal sarcopenia have been associated to malnutrition and undernutrition, which in turn is accompanied by several alterations detectable in blood regarding both blood cell counts and biochemical metabolic markers [20–23] we also evaluated the associations between the parameters related to respiratory muscle strength and skeletal sarcopenia with blood cell counts and biochemical parameters related to protein, lipid, glucose and indirectly with energy production (glucose, creatinine, transaminases, and ions concentrations).

#### **2. Materials and Methods**

#### *2.1. Design and Study Population*

A cross-sectional study was conducted in individuals institutionalized in nursing homes and long-stay centers for the older individuals in the province of Valencia, Spain (GeroResidencias La Saleta, Valencia). We selected nursing home residents of both genders. Participants were excluded if they were unable to understand the content of questionnaires (moderate-severe cognitive impairment), had a poorly controlled major psychiatric disease (schizophrenia, bipolar disorders, etc.), acute infections, or a known cancer condition. According to the requirements of the Declaration of Helsinki, written consent was obtained from all of the selected subjects before beginning the study, after informing them about the procedures involved and the purpose of the research. The entire study protocol was

approved by the local ethical committee at the University of Valencia (H1524420647893, approved 5 July 2018).

#### *2.2. Sociodemographic and Clinical Variables*

Socio-demographic variables and medical conditions were recorded, including the number of medications taken, the type and number of any comorbidities using the Charlson index, and several hematological and biochemical parameters. The Charlson index was used to assess comorbidity (with a Cronbach's Alpha of 0.78) [24]. This index assesses 16 diseases that are explicitly defined and scored by a continuous variable from 0 to 31. With this index, the 10-year survival prediction is estimated for patients with comorbidity [25].

#### *2.3. Measurement of Respiratory Muscle Function*

The assessment of respiratory function was carried out through two different tests, the assessment of lung volumes and flows by performing a forced spirometry, and the assessment of the maximum respiratory pressures that the respiratory muscles are capable of generating at mouth level as a result of maximum effort.

The spirometric assessment followed the standardized recommendations of the European Respiratory Society [26]. The patient was placed in a seated position, with his back supported by the backrest and with nasal clamps to avoid air leakage. The maneuver was explained in detail to the patient to minimize errors, requesting an initial maximum inspiration to reach total lung capacity, which allows the subsequent performance of a forced maximum expiration for at least 6 s, until the limit of expiration is reached. At least three manoeuvres are performed, with a rest of 1 min between each one, and the highest value of the three repetitions is recorded.

By carrying out this test, the following volumes and forced pulmonary capacities in absolute and relative values were obtained: forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), FEV1/FVC, forced expiratory volume in smaller than 1mm diameter tracks (FEV2575) and peak expiratory flow (PEF). At least three repetitions of the maneuver were performed (with a maximum of 8 repetitions) to achieve the correct execution of the test, discarding those spirometric maneuvers with artifacts in their performance or variations of more than 0.150 L between the highest FEV1 and/or FVC values, as recommended by the ATS/ERS [26].

For the assessment of respiratory muscle strength, maximum static respiratory pressures in the mouth, inspiratory (MIP) and expiratory (MEP) were measured. These parameters allow us to know in a simple way the global force that the respiratory muscles are capable of exerting. The tests require the collaboration of the patient to perform a maximum isometric effort. The standardized regulations for this test were followed [27,28]. To evaluate the MIP, the patient was instructed to start from the residual volume and for the MEP to start from the total lung capacity, so that the maximum value of the three maneuvers could be collected, with a variation of less than 10% between them and a 1-min pause between each of the repetitions. This excluded those attempts where there was more than 10% variation between them, as recommended by Laveneziana, et al. [28].The proposed cut-off points for PEF and maximum respiratory pressures (MIP and MEP) were used to establish the existence of respiratory sarcopenia. The cut-off point for PEF was set at 4.40 L/s for men and 3.21 L/s for women [22]. The cut-off point for MIP was set at less than or equal to 55 H2O cm for men and less than or equal to 45 H2O cm for women, while for MEP it was set at less than or equal to 60 H2O cm for men and less than or equal to 50 H2O cm for women [4]. Before the test was conducted, the steps for correctly performing the test were carefully explained to the participants. Once explained, a test of all the steps to be followed was carried out, without demanding maximum effort from the participants to avoid accumulated fatigue. Afterwards, the tests were carried out in accordance with international standards [28].

The older institutionalized population has a high prevalence of cognitive impairment, which could make this type of testing difficult. However, we excluded patients with moderate and severe cognitive impairment, so that the collaboration of patients included was adequate to perform these tests. In addition, an adaptation procedure was carried out on the study subjects before the definitive test, excluding from the sample those subjects who presented poor coordination and, therefore, difficulty in carrying out the test at the discretion of the evaluator. In all the centres, assessments were made in the morning between 8 and 11 am and in the same period of time. To avoid inter-observer errors, all measurements were taken by the same trained investigator.

In addition, to analyze reliability, we assessed the stability of the measure obtaining values of intraclass correlation coefficient (ICC; one-way, mixed-effects model) between PEF values in the three centers of 0.71, what was indicative of moderate to good reliability.

#### *2.4. Measurement of Sarcopenia*

Muscle skeletal sarcopenia was assessed by indirect measures of muscle function and muscle mass, such as handgrip strength assessed by hand-dynamometry, walking speed and bioimpedance respectively. Hand-dynamometer was assessed in the dominant hand by means of a JAMAR dynamometer (Lafayette Instrument Company, Lafayette, IN, USA) as previously described [29]. The subject was placed in a standard position: in a sitting position, with the shoulder at 0◦ of flexion, the elbow attached to the body at 90◦ of flexion and the forearm in a neutral position. After the subject is positioned appropriately, the examiner asks the patient to squeeze as hard as possible for 3 s and then relax. Three attempts were made, with 1 min rest in between. The mean value obtained was recorded. The cut-offs for handgrip strength were <sup>≤</sup>30 kg/m<sup>2</sup> for men and <sup>≤</sup>20 kg/m<sup>2</sup> for women [2]. The walking speed was assessed using the 4-m walking test [30]. The patient was asked to walk at usual pace and from a standing start and using their usual walking aid. The time required to cover this distance was recorded and, based on this, the walking speed in m/s was calculated. The cut-off for low walking speed was ≤0.8 m/s walking through 4 m [2]. The body composition was assessed by bioelectrical impedance analysis (BIA) with a BF-300 device (Tanita, Tokyo, Japan) as previously described [31,32]. The BIA measure was performed with a standard technique using a single frequency of 50 KHz and 550 mA, and the placement of four electrodes in a distal position (four electrodes at feet) while participant was in a standing position. BIA measurements were carried out in the early morning following the next considerations: (1) No physical exercise in the previous hours; (2) 2–3 h of fasting, including drinking plenty of water or alcohol; (3) urination 30 min before the test; (4) no metal parts at the time of the test. The values of reactance and resistance were then recorded once the patient was stabilized. The repeatability and accuracy of the resistance and reactance measurements enabled the smallest changes to be recorded to a resolution of 0.1 Ω. Muscle mass was calculated using the formula of Janssen et al. [31]: muscle mass (kg) = [(height<sup>2</sup> /R × 0.401) + (3.825 × sex) + (−0.701 × age) + 5.102] where height is expressed in cm, R in Ω, age in years and female sex has a value of zero and males a value of one. The muscle mass index (MMI) is defined as the muscle mass a person has, corrected by body surface area (muscle mass/height<sup>2</sup> ). The bioimpedance test was performed early in the morning while the patient is at rest, after overnight fasting (food and drink) and removing all metal elements. The cut-off for the loss of muscle mass assessed by bioimpedance of the whole body were <sup>≤</sup>5.5 kg/m<sup>2</sup> for women and <sup>≤</sup>7.25 kg/m<sup>2</sup> ) for men [2]. These muscle mass values are adjusted with the cut-off values for the Spanish population being 8.31 kg/m<sup>2</sup> for men and 6.68 kg/m<sup>2</sup> for women [33]. In order to minimize the influence of physical performance across the time of the day, all measurements were always conducted between 8–11 a.m.

#### *2.5. Haemogram and Analytical Parameters*

To obtain the analytical determinations, the usual blood controls carried out in residential centers were used. Thus, blood samples were collected from each subject at approximately 8 am (after 8–10 h fasting). 10 mL of blood plasma was collected into Vacutainer tubes (BD, Franklin Lakes, NJ, USA) containing EDTA.

Clinical laboratories belonging to local public health centers were used to analyze the different hematological parameters (white blood cells, hemoglobin, erythrocytes, and platelets) and biochemical parameters (glucose, urea, urate, cholesterol, triglycerides, creatinine, glutamic oxaloacetic transaminase [GOT], and serum glutamic pyruvic transaminase [GPT], sodium ions [Na+], potassium ions [K+], and Calcium [Ca++]). Within public health centers, the variation range of metabolites in plasma sample varies between 0.4–1.1% dependent on the metabolite.

#### *2.6. Statistical Analysis*

Quantitative variables were analysed using descriptive statistics, specifically central tendency measures (means), standard error of the mean (SEM), 95% confidence interval and ranges. Frequencies and percentages were used to describe the qualitative variables. The normal distribution of the variables, in order to determine whether to carry out parametric or non-parametric tests, was analysed using the Shapiro-Wilk test. Outliers were identified on the boxplot drawn in SPSS program which uses a step of 1.5 × IQR (Interquartile range). No outliers were identified and all data were included in the statistical analysis. Differences in quantitative variables between the two groups were analyzed with the two-tailed tests e.g., parametric Student t-test or the nonparametric Mann-Whitney U-test. To analyze the correlation between quantitative variables, the parametric Pearson test or the non-parametric Spearman's test was used depending on their distribution. Statistical significance was considered at *p* < 0.05. SPSS version 25.0 statistical package (SPSS Inc., Chicago, IL, USA) was used to perform the statistical analyses.

#### **3. Results**

#### *3.1. Sociodemographic and Clinical Parameters of the Study Sample*

A total of 58 subjects (67.2% female) living in three nursing care centers located in the province of Valencia (Spain) were enrolled in the study (Table 1). All the participants were Caucasian. Their age ranged from 55 to 93 years, and the mean age was 78.6 ± 8.9 years. 63.8% of the subjects were independent in their walking ability (they did not require external aids such as a cane or walker). Smokers were 15.5% (*n* = 9) of the sample. A percentage of 21.1% (*n* = 12) in the study sample used bronchodilators as a usual treatment. Among individuals using bronchodilators, *n* = 6 used bronchodilator therapy containing glucocorticoids. Regarding the use of common medications affecting the muscular system, none of the individuals received oral glucocorticoid treatment, 37.9% (*n* = 22) used statins to lower cholesterol levels and 5.2% (*n* = 3) used muscle relaxant drugs. Mean body mass index was 28.8 ± 5.8 (Range 18.7–50.2). The Charlson comorbidity index score adjusted for age was 5.4 ± 1.9 (Range 1.0–11.0). The occurrence of the most common comorbidities are indicated in Table 1.

Respiratory function assessment showed an absence of respiratory failure related to oxyhemoglobin saturation, with 95.9 ± 1.9% (range 91.0–99.0). Respiratory functional exploration showed spirometric values within normal ranges for a population of these characteristics (FVC at 84.0 ± 23.6% (Range 23.0–149.0) and FEV1 at 83.3 ± 28.3% (Range 20.0–160.0)), except for a small reduction in the permeability of the smaller diameter airway, with an FEV2575 at 54.5 ± 25.7% (Range 12.0–149.0). Respiratory muscle strength was diminished, at both inspiratory (36.5 ± 17.4 H2O cm) and expiratory (58.9 ± 23.7 H2O cm) levels. The maximal respiratory pressures (MIP and MEP) and spirometric parameter values (FVC, FEV1, FEV1/FVC, FEV2575 and PEF) are shown in Table 2.

A positive correlation was found between oxyhemoglobin saturation and FVC (r = 0.287 *p* = 0.034, Pearson test) and oxyhemoglobin saturation and FEV1 (r = 0.269 *p* = 0.047, Pearson test). No correlations were found between heart rate and any other respiratory parameters.


#### **Table 1.** Characteristics of the study sample.

**Table 2.** Respiratory function parameters.


A positive correlation can be found between the various parameters that describe the spirometric function by analyzing the correlation between the different parameters of respiratory function. There was a significant correlation between FVC percentage values and FEV1 percentage values (r = 0.894, *p* < 0.001, Pearson test), FEV2575 percentage values (r = 0.473, *p* < 0.001, Pearson test) and PEF (r = 0.281 *p* = 0.033, Pearson test). Significant correlations were also found between FEV1 percentage values and FEV2575 percentage values (r = 0.689, *p* < 0.001, Pearson test). There was a correlation between PEF and maximum respiratory pressures, with both MIP (r = 0.419, *p* < 0.001, Pearson test) and with MEP (r = 0.575, *p* < 0.001, Pearson test), and the maximum respiratory pressures between them (r = 0.559, *p* < 0.001, Pearson test).

Based on the PEF cut-off points established by Kera et al., (22), the prevalence of respiratory sarcopenia in the sample studied was 70.7%. On the other hand, if the values of MIP and MEP established by Ohara et al., (4) are taken as the benchmark, the prevalence of respiratory sarcopenia was 80.7% and 37.9%, respectively.

#### *3.2. Evaluation of Skeletal Muscle Mass and Function*

According to the EWGSOP guidelines, 17.6% of the subjects were classified as sarcopenic, with 17.6% meeting the criteria of reduced lean mass, 65.4% meeting the criteria of low physical performance and 84.5% meeting the criteria of reduced muscle strength. The mean values of each criterion were skeletal muscle-mass index of 9.21 <sup>±</sup> 2.793 kg/m<sup>2</sup> , walking speed of 0.66 ± 0.331 m/s

and handgrip strength of 17.90 ± 8.506 kg. The data from the anthropometric characteristics of all the participants in this study are summarized in Table 3.


**Table 3.** Anthropometric analysis and sarcopenia parameters.

*3.3. Evaluation of the Relationship between Muscle Skeleñata Parameters (Mass and Function) and Muscle Respiratory Function*

There was a significant and positive correlation between physical performance and PEF absolute values (r = 0.563, *p* < 0.001, Spearman's test), PEF percentage values (r = 0.440, *p* = 0.001, Pearson test) and MIP values (r = 0.354, *p* = 0.011, Spearman's test). No correlation between physical performance and MEP was found (r = 0.268, *p* = 0.268, Spearman's test). No significant correlation was found between the other parameters of respiratory function and physical performance (*p* > 0.05 in all cases).

There was a significant and positive correlation between handgrip strength and MIP values (r = 0.599, *p* < 0.001, Spearman's test), MEP values (r = 0.465, *p* < 0.001, Spearman's test) and PEF absolute values (r = 0.375, *p* = 0.004, Spearman's test). There was also a significant but negative correlation between handgrip strength and FEV1 percentage values (r = −0.307, *p* = 0.019, Spearman's test). No significant correlation was found between other parameters of respiratory function and handgrip strength (*p* > 0.05 in all cases) (Figure 1). −

**Figure 1.** Representation of the significant correlations between skeletal and respiratory muscle sarcopenia parameters. Significant correlations between gait speed and PEF (**A**) or MIP (**B**) and between handgrip strength and PEF (**C**) or MIP (**D**).

No significant correlations were found between skeletal muscle mass index and respiratory function parameters, in relation to either PEF absolute values (r = 0.252, *p* = 0.074, Spearman's test), or MIP (r = 0.143, *p* = 0.322, Spearman's test), or MEP (r = 0.225, *p* = 0.112, Spearman's test).

We categorized patients based on cut-off scores for skeletal sarcopenia (see Methods section) and we evaluated whether there were any differences in the respiratory parameters and respiratory muscle parameters (Figure 2). −

**Figure 2.** Mean difference of respiratory parameters ((**A**): FEV1; (**B**): PEF; (**C**): MIP; (**D**): MEP) according to the presence or not of the three cut-off values for sarcopenia parameters \* *p* < 0.05; \*\* *p* < 0.001.

As for physical performance, differences were observed in both PEF (NS = 3.78 vs. S = 2.49, MeanDiff = 1.29 [95%CI: 0.67–1.91], *p* < 0.001) and PEF% (NS = 64.11 vs. S = 47.21, MeanDiff = 16.90 [95%CI: 6.59–27.22], *p* = 0.002).

For the handgrip strength, different maximal respiratory pressures were observed in both groups, MIP (NS = 54.89 vs. S = 33.06, MeanDiff = 21.83 [95%CI: 10.48–33.18], *p* < 0.001) and MEP (NS = 73.22 vs. S = 56.69, MeanDiff = 16.92 [95%CI: 0.13–37.70], *p* = 0.048). When analyzing the PEF we observed no statistically significant differences, although a trend was observed in them (NS = 3.57 vs. S = 2.74, MeanDiff = 0.86 [95%CI: −0.006–1.72], *p* = 0.052)

No significant differences for lean mass content were observed for any of the comparisons (*p* > 0.05) (Figure 2).

We also categorized patients based on respiratory muscle sarcopenia according to Kera et al. (22) and Ohara et al. (4) (see methods), and we evaluated whether there were any differences in the somatic sarcopenia parameters, such as skeletal muscle mass index, handgrip strength and gait speed (Figure 3).

− For MIP, differences were observed in both gait speed (NS = 0.89 vs. S = 0.59, MeanDiff = 0.30 [95%CI: 0.51–0.85], *p* = 0.007) and handgrip strength (NS = 27.35 vs. S = 15.64, MeanDiff = 11.71 [95%CI: 4.75–18.66], *p* = 0.003). No differences were found for skeletal muscle mass index (*p* = 0.844).

As regards MEP, a different maximal handgrip strength were observed in both groups, (NS = 20.31 vs. S = 13.96, MeanDiff = 6.35 [95%CI: 2.59–10.11], *p* = 0.001). No statistically significant differences were found in gait speed or skeletal muscle mass index (*p* = 0.156 and *p* = 0.214, respectively).

For PEF, differences were observed in gait speed (NS = 0.82 vs. S = 0.58, MeanDiff = 0.24 [95%CI: 0.32–0.45], *p* = 0.025), but not in handgrip strength (NS = 17.90 vs. S = 17.90, MeanDiff = 0.01 [95%CI: −4.99–4.98], *p* = 0.997) (Figure 3).

−

**Figure 3.** Mean difference of muscle mass (**A**), Handgrip strength (**B**) and gait speed (**C**) according to the presence of each respiratory muscle sarcopenia criteria. \* *p* < 0.05; \*\* *p* < 0.001.

#### *3.4. Evaluation of the Relationship between Sarcopenia Parameters and Blood Analytical Markers*

No significant associations were found when analyzing the possible correlations between the parameters of the hemogram (white blood cells, hemoglobin, erythrocytes, and platelets) and the parameters of respiratory sarcopenia and somatic sarcopenia (*p* > 0.05 in all cases).

− The relationship between respiratory sarcopenia parameters and biochemical parameters (glucose, urea, urate, cholesterol, triglycerides, creatinine, glutamic oxaloacetic transaminase [GOT], and serum glutamic pyruvic transaminase [GPT], sodium ions [Na+], potassium ions [K+], Calcium [Ca++]) was subsequently studied. There was a significant and positive correlation between PEF values and GOT (r = 0.387, *p* = 0.004, Spearman's test) and a significant and negative correlation between PEF values and urea (r = −0.366, *p* = 0.007, Pearson test) (Figure 4). No significant correlation was found between other parameters of biochemical markers and respiratory sarcopenia parameters values (*p* > 0.05 in all cases, Pearson's and Spearman's correlation test).

We also categorized patients based on criteria of respiratory sarcopenia according to Kera et al. (22) and Ohara et al. (4) (see methods) and we evaluated whether there were any differences on blood analytical markers.

Significant differences were found in urea values for the presence of sarcopenia estimated by PEF (NS = 32.58 vs. S = 46.70, MeanDiff = 14.12 [95%CI: −23.59–4.64], *p* = 0.005) but not in GOT values (NS = 18.50 vs. S = 14.97, MeanDiff = 3.53 [95%CI: −1.18–8.23], *p* = 0.132).

−

**Figure 4.** Correlation between PEF and urea (**A**) and GOT (**B**) concentration. −

Studying the possible correlations between somatic sarcopenia values and biochemical parameters showed a significant and positive correlation between handgrip strength and urate concentration (r = 0.279, *p* = 0.041, Spearman's test) and between gait speed and GOT (r = 0.390, *p* = 0.006, Spearman's test). There was also a significant and negative correlation between skeletal muscle mass index and total cholesterol (r = −0.405, *p* = 0.004, Spearman's test) and triglycerides (r = −0.357, *p* = 0.017, Spearman's test), and between urea and gait speed (r = −0.36, *p* = 0.012, Spearman's test). No significant correlation was found between other parameters of biochemical markers and muscle mass and function values (*p* > 0.05 in all cases, Spearman's correlation test) (Figure 5). − − − −

**Figure 5.** Correlation between skeletal muscle sarcopenia parameters and urea (**A**), GOT (**B**) and lipids ((**C**): total cholesterol; (**D**): triglycerides) concentration in blood.

We also categorized the patients based on the cut-off scores of the three parameters studied for the evaluation of sarcopenia (see Methods section) and evaluated if there were any differences in blood analytical markers.

− −

−

−

−

For the gait speed, there were statistically significant differences in urea values (NS = 34.72 vs. S = 45.82, MeanDiff = 11.10 [95%CI: −20.44–1.76], *p* = 0.042) but not in GOT values (NS = 17.0 vs. S = 16.42, MeanDiff = 0.58 [95%CI: −2.31–3.48], *p* = 0.685).

For the presence of sarcopenia according to lean mass content, there were statistically significant differences in total cholesterol values (NS = 162.29 vs. S = 199.13, MeanDiff = 36.83 [95%CI:−71.58—2.08], *p* = 0.04) but not in tryglicerides (NS = 135.92 vs. S = 180.75, MeanDiff = 44.83 [95%CI: −99.94–10.27], *p* = 0.101)

As for handgrip strength, no differences were observed in urate values between groups (NS = 4.74 vs. S = 4.79, MeanDiff = 0.05 [95%CI: −0.94–0.85], *p* = 0.807).

#### **4. Discussion**

This study, which analyzes sarcopenia parameters in older people living in nursing homes, shows the direct relationship between respiratory muscle function and skeletal muscle function, especially with regard to the muscular strength and walking speed, and we report on the correlation between sarcopenia parameters and several biochemical markers obtained in routine blood analysis. This is the first study, to our knowledge, that considers the relationship between respiratory muscle strength and blood biochemical markers, finding a relationship between peak expiratory flow (PEF) values and glutamate-oxaloacetate transaminase (GOT) and urea concentration. We also observed associations between musculoskeletal parameters of sarcopenia with some blood markers, e.g., muscle mass and total cholesterol and triglyceride values, walking speed and urea and GOT values and handgrip strength and urate values. We discuss these new findings below.

The prevalence of sarcopenia in the sample of nursing home residents, following the EWGSOP criteria [2] and adjusting the skeletal muscle mass index to the Spanish population according to the cut-off points proposed by Masanés and coworkers [33], was 17.6%. These data are lower than those previously proposed for the Spanish institutionalized population [8], 41.4% applying the same assessment criteria, but are consistent with those described in a literature review that includes studies in several countries of patients residing in long-term care homes [6], like the population of our study. It is possible that the exclusion of patients who were not able to understand the content of the questionnaires influences the prevalence of the sample in the present study, since the presence of cognitive impairment increases the rates of sarcopenia [34].

The relationship between respiratory function parameters and somatic sarcopenia in community-dwelling older people has been studied in recent years, given the objectivity of these parameters and the ease and speed of assessment, but no studies in nursing home residents displaying higher levels of functional impairment and comorbidity burdens have been reported. Three parameters of respiratory function that have been established in the literature as determinants of respiratory sarcopenia, PEF [35] and maximum inspiratory (MIP) and expiratory (MEP) respiratory pressures [4].

Prevalence scores of respiratory sarcopenia according to PEF values were 70.7%, while maximum respiratory pressures were 80.7% according for MIP and 37.9% for MEP. The highest prevalence values of respiratory sarcopenia were obtained for both MIP and PEF, as in the study by Bahat et al. [36]. This may be due to the fact that loss of respiratory muscle strength occurs first in the inspiratory muscles, and is related to deterioration of type IIx and/or IIb muscle fibers of the diaphragm [3]. Loss of inspiratory muscle strength (MIP) leads to a reduced volume of inspired air prior to glottal closure and contraction of the expiratory muscle, preventing effective maximal expiration (PEF) [37,38]. In addition, it implies an inability to fully inflate the lungs, which is necessary to achieve the optimization of the length-tension relationship of the expiratory muscles, stimulate lung surfactant production and distribution, and open the collapsed peripheral airways that often accompany the hypoventilation processes associated with age and the aging process [39–41].

Furthermore, the greater relevance of the inspiratory muscles in the deterioration of the peripheral muscles was also justified by the decline in handgrip strength (84.5% of the sample studied) and the decline in walking speed (65.4% of the sample studied), as established in previous studies [4,19].

PEF was considered the most relevant parameter for establishing respiratory sarcopenia by Kera et al. [35,42] due to the involvement of the respiratory muscles in its execution and the minimal impact of the deterioration of the airway on its values, since it is measured at the beginning of forced expiration, and is not affected by the modifications in elastic recoil and thorax compliance associated with age [43]. The authors highlighted their preference for this test over respiratory muscle strength because of the lesser effort required and to avoid maneuvers that involve an increase in intracranial pressure, with the risks that this entails [35].

The results of this study confirm the results obtained by Kera et al. [42] in community-dwelling older people, but obtain higher values of correlation than Kera in the criterion of strength (handgrip strength) (r = 0.375 vs. r = 0.283) and in the criterion of functional performance (gait speed) (r = 0.563 vs. r = 0.167). No correlation was obtained in this study with the index of musculoskeletal mass, with muscle function more relevant than the amount of existing lean muscle mass in sarcopenic older individuals. In turn, Kera et al. [35] obtained differences between patients categorized as respiratory sarcopenic for the three determining variables of somatic sarcopenia, which were always higher in non-sarcopenic patients, while these differences were only obtained for gait speed in this study, possibly due to the high rates of sedentarism among nursing home residents and their more limited independence in their basic activities of daily life. In our study, no associations were found between respiratory muscle function and lean mass content and it could be explained in part by the obesity paradox [44]. The body mass index in the study sample widely varies among the participants enrolled in the study (range 18.7–50.2) and one third of patients have overweight and obesity grade I. This paradoxical benefit of a medically unfavorable phenotype is particularly strong in the overweight and class I obesity, and less pronounced in the more severe or morbidly obese populations (class II–III and greater). Rather than an obesity paradox, it is possible that this phenomenon may represent a "lean paradox", in which individuals classified as normal weight or underweight may have a reduced lean mass, as a result of a progressive catabolic state and lean mass loss [45–47] whereas overweight and obese patients maintain an adequate lean mass content compared to under and normo-weight individuals [44,48]. Likely, the reduced respiratory muscle strength in overweight and obese individuals could be explained by other pathophysiological factors related to excessive fat accumulation in the thoracic-abdominal region which limits the chest wall expansion and diaphragm contraction, lengthens abdominal muscles, reduces the upper airway calibre, modifies airway configuration, and increases in intra-abdominal pressure and these effects may reduce respiratory muscle function independently on lean mass content [49–51]. Alternatively the reduced muscular function in obese individuals may be also related to chronic low-grade inflammation characterized by the predominance of interleukin-1β, interleukin-6, and tumor necrosis factor-α (TNF-α) observed in obese patients [52]. Further studies with larger sample should evaluate in details the comparison the effects of underweight, obesity with or without sarcopenia on respiratory muscle strengths in order to shed new lights on these apparent discrepancies between muscular strength and lean mass content.

Other reports suggested that valuable markers of reduced respiratory muscle strength are the values related to the maximum respiratory pressures (MIP and MEP), because these parameters are a more direct measurement of the maximum strength of respiratory muscles [4,19,36,53]. In our study, MIP correlated with both walking speed and handgrip strength (r = 0.599 and r = 0.354, respectively), while MEP correlated with handgrip strength (r = 0.465). This parameter, which is slightly more difficult to evaluate than the PEF due to its assessment procedure, is directly related to the loss of strength in the peripheral muscles, as seen in previous studies not only of older people living in the community [19,53] and in nursing homes [4], but also in healthy [54] and hospitalized young adults [55]. On the other hand, no relationship could be found between skeletal muscle mass index and maximum respiratory pressures, like those reported in previous studies of healthy older patients [53] and older patients with cardiovascular diseases [19].

These parameters of maximum respiratory strength appear to be good indicators of reduced respiratory muscle strength in older institutionalized individuals, since patients who presented sarcopenia according to these cut-off values presented significantly lower values of gait speed and handgrip strength that were as good as those recently shown by community dwelling older adults [4].

We demonstrated that parameters related to reduced respiratory muscle strength, e.g., PEF values, are significantly associated with urea and GOT concentrations in blood, which have not been previously reported for the respiratory muscle function. GOT, also known as aspartate aminotransferase, is a mitochondrial and cytoplasmic enzyme, with an important role in cell energy production [56]. Alterations in GOT levels in blood are considered well-known markers of hepatic, myocardial and skeletal muscle cytolysis, while GPT also known as alanine aminotransferase, is mainly a hepatic cytoplasmic enzyme [57–59]. In our study, the lack of a significant association between PEF and GPT levels in blood suggests that the association between PEF and GOT levels is related to myocardial or skeletal muscle metabolism. High serum GOT with normal serum GPT is highly prevalent among community dwelling older individuals who are underweight, and might reflect skeletal muscle pathology [60]. Furthermore, high levels of GOT in serum are present in obese subjects, regardless of age, which may be associated with sarcopenic obesity, reduced muscle mass and overweight, in some of the subjects studied [61,62]. However, the processes involved in regulating blood GOT levels in both underweight and obese subjects remain unknown, but they seem to be related to low muscle mass and function, and in this respect we found a new association with PEF values. The role of cardiac diseases cannot be ruled out, since 30% of the sample presents a comorbidity of this type. However, due to the limited size of the sample of nursing home residents with preserved cognitive function necessary to perform spirometry analysis, it was impossible to study selective pathologies.

However, confirming the association between GOT levels and muscular metabolism and function, GOT levels were also found to be significantly associated with gait speed and almost significantly with grip strength (*p* = 0.05). PEF values were also inversely and significantly associated with urea concentration in blood. Elevated serum urea, a breakdown product of protein, is generally considered a marker of muscle wasting in several conditions [63,64]. Another possible explanation for increased urea levels could be an alteration in kidney function, but the creatinine levels in our study were not significantly associated with any of the sarcopenia parameters and the correlation between urea levels and PEF therefore suggested effects based on muscle metabolism. A recent study with a machine learning approach found that urea concentration is one of risk factors for the development of predictive models for patients with sarcopenia [65], and we also reported an association between urea levels and gait speed. In relation to the positive correlation between uric acid levels and muscle strength reported in our study, this finding replicates the association reported in community dwelling-older individuals in the "InCHIANTI" study [66], which observed that higher urate levels were significantly associated with higher measures of muscle strength, and concluded that high urate levels could create a protective reaction that would counteract the excessive production of free radicals that damage muscle proteins and reduce muscle strength. Likewise, Can et al. [67], focusing on markers of inflammation and oxidative stress, analyzed a sample of 72 geriatric patients confirmed that patients with sarcopenia had significantly lower levels of uric acid than non-sarcopenic patients. Moreover, high serum urate levels are a good positive predictor of grip strength in nonagenarian older individuals, and may delay the progression of sarcopenia [68]. The skeletal muscle criterion of lean mass content was the only criterion that was significantly (and inversely) correlated with blood lipid (cholesterol and triglycerides) concentration. The aging process stimulates the appearance of fat infiltration in muscle tissue, and obesity enhances fat deposits at visceral level, in the liver, heart, pancreas and skeletal muscle, which generates a negative effect on sarcopenia. These lipids cause a pro-inflammatory effect that secretes paracrine and cytokine hormones, promoting a feedforward cycle by producing intramyocellular lipids. This toxicity generated by fats hinders the contraction of muscle fibers and the synthesis of muscle proteins, favoring the development of sarcopenia [69,70].

A study by the South Korean KNHANES conducted an evaluation of sarcopenic obesity subjects and showed a link to an increased risk of dyslipemia in these patients [71]. Mesinovic et al. [72] recently determined the associations between metabolic syndrome and components of sarcopenia, including

muscle mass and quality, absolute and relative strength, and physical performance, in 84 overweight and obese older adults, and demonstrated that triglyceride levels had a negative association with leg extension strength and lower-limb relative strength. Lu et al. [73] reported that serum triglycerides and high-density lipoprotein cholesterol were independently associated with sarcopenic obesity. All the biomarkers found to be significantly associated with sarcopenia indexes can be obtained in a routine blood analysis, as they can be rapidly, inexpensively, and reproducibly assayed. Future longitudinal investigations should test these biomarkers as a part of a valuable panel of metabolites to diagnose sarcopenia and monitor the efficacy of clinical interventions in sarcopenic individuals. This is the first study to demonstrate an independent relationship between respiratory muscle strength and some aspects of body sarcopenia in institutionalized elderly people with high rates of comorbidities and polypharmacy. The fact that respiratory sarcopenia is associated with muscle strength and gait speed supports the beneficial effect of various exercises and rehabilitation interventions on breathing muscles [74–76]. New randomized clinical trial should evaluate the effects of such interventions not only for skeletal sarcopenia but also to improve respiratory muscle strength thus allowing a better respiratory function which can influence many respiratory tract diseases since the impairment of (inspiratory and expiratory) respiratory muscles is a common clinical finding, not only in patients with neuromuscular disease but also in those with respiratory diseases affecting the lung parenchyma or airways [77–79]. We provided further evidence for the use of suitable cut-off points for respiratory muscle strength which can be tested in future researches prior its proposal as indicator of muscle respiratory function in clinical settings. Loss of mass and function of the respiratory muscles could be prevented by properly applying these exercises. More studies on sarcopenia and its effects on respiratory muscle strength are needed to improve life expectancy and quality of life in the older institutionalized individuals.

**Author Contributions:** Conceptualization, F.M.M.-A., C.B., R.F.-V., O.C.; Methodology, F.M.M.-A., C.B., R.F.-V., O.C.; formal analysis, F.M.M.-A., O.C.; investigation, F.M.M.-A., C.B., R.F.-V., O.C.; data curation, F.M.M.-A., C.B., R.F.-V., O.C.; writing—Original draft preparation, F.M.M.-A., O.C.; writing—Review and editing, F.M.M.-A., C.B., R.F.-V., O.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**


#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **Preserved Capacity for Adaptations in Strength and Muscle Regulatory Factors in Elderly in Response to Resistance Exercise Training and Deconditioning**

**Andreas Mæchel Fritzen 1,2,\* , Frank D. Thøgersen <sup>1</sup> , Khaled Abdul Nasser Qadri <sup>1</sup> , Thomas Krag <sup>1</sup> , Marie-Louise Sveen 1,3, John Vissing <sup>1</sup> and Tina D. Jeppesen <sup>1</sup>**


Received: 4 June 2020; Accepted: 9 July 2020; Published: 10 July 2020

**Abstract:** Aging is related to an inevitable loss of muscle mass and strength. The mechanisms behind age-related loss of muscle tissue are not fully understood but may, among other things, be induced by age-related differences in myogenic regulatory factors. Resistance exercise training and deconditioning offers a model to investigate differences in myogenic regulatory factors that may be important for age-related loss of muscle mass and strength. Nine elderly (82 ± 7 years old) and nine young, healthy persons (22 ± 2 years old) participated in the study. Exercise consisted of six weeks of resistance training of the quadriceps muscle followed by eight weeks of deconditioning. Muscle biopsy samples before and after training and during the deconditioning period were analyzed for MyoD, myogenin, insulin-like growth-factor I receptor, activin receptor IIB, smad2, porin, and citrate synthase. Muscle strength improved with resistance training by 78% (95.0 ± 22.0 kg) in the elderly to a similar extent as in the young participants (83.5%; 178.2 ± 44.2 kg) and returned to baseline in both groups after eight weeks of deconditioning. No difference was seen in expression of muscle regulatory factors between elderly and young in response to exercise training and deconditioning. In conclusion, the capacity to gain muscle strength with resistance exercise training in elderly was not impaired, highlighting this as a potent tool to combat age-related loss of muscle function, possibly due to preserved regulation of myogenic factors in elderly compared with young muscle.

**Keywords:** resistance exercise training; muscle regulatory factors; sarcopenia; muscle strength; deconditioning; skeletal muscle; elderly; hypertrophy

#### **1. Introduction**

Sarcopenia means loss of flesh. The term is used to describe the pathological age-related loss of muscle mass, function, and strength that inevitable occurs in humans [1]. From the age of 50 to 85, humans lose 50% of their muscle mass, which is mainly a result of loss of type II muscle fibers [2]. Age-related loss of muscle mass and strength is associated with increasing risk of falling and disability, and thus impairment of basic daily activities.

It is well established that resistance exercise training can counteract the age-related changes in contractile function, strength, hypertrophy, and morphology of aging skeletal muscle [3]. However, whether the potential to adapt to resistance exercise training is completely preserved in skeletal

muscles of elderly has been debated. [3]. Although 6–10 weeks of exercise training increased skeletal muscle strength to a similar extent in young and elderly in some studies [4,5], others report greater improvements in young individuals [6,7]. The rate of decline in muscle strength with age is 2–5 times greater than declines in muscle size [8] and strength loss is highly associated with both mortality and physical disability, even when adjusting for sarcopenia, indicating that muscle mass loss may be secondary to the effects of strength loss [9]. It is thus of key interest to elucidate whether increased muscle strength after a period of resistance exercise training occurs to a similar or blunted extent in old compared to young muscle. Moreover, although an aged-associated loss of muscle mass or strength [10,11] appears improved with resistance training in elderly individuals [12–16], several studies find a blunted muscle hypertrophy response [17–19].

Mechanisms responsible for resistance exercise-induced muscle hypertrophy are numerous, but some of the key factors include MyoD, myogenin, and insulin-like growth factor-I (IGF-I) [20–22]. The myogenic regulatory factors (MRF) are transcription factors that promote and regulate the expression of muscle-specific genes, which are essential to the hypertrophic and regenerative response following resistance exercise [23–26]. As MyoD is highly involved in muscle adaptation to resistance exercise, this has been a key factor in studies investigating potential differences in age-related muscle loss [27–29]. Differences in MRFs between young and elderly could be crucial mechanisms behind differences in muscle mass and strength [22,23,30] and in the response to resistance training and deconditioning. Previous studies found elevated levels of MyoD, myogenin, and IGF-I-R mRNA in elderly both at rest [17,31–34] and in response to one bout of resistance exercise [11]. Moreover, 16 weeks of resistance training increased muscle myoD mRNA levels to a similar extent in young and elderly, whereas the training-induced increase in mRNA levels of myogenin was impaired in the elderly [17].

Proteins responsible for negative muscle mass regulation, e.g., actRIIB and smad2, could be upregulated in inactive, aged muscle and be attenuated in response to resistance exercise, resulting in decreased muscle mass. In support, the mRNA level of actRIIB was downregulated after 21 weeks of resistance exercise in elderly [35,36]. The regulation of these molecular pathways involved in negative muscle mass regulation in response to resistance training in young and old muscle is unknown.

Mitochondrial dysfunction is another suggested key contributor loss of muscle mass with age [30]. Resistance exercise training has been found to affect mitochondrial function [37] evidenced by improved mitochondrial respiration and complex protein content after 12 weeks of resistance exercise training in young men [38]. However, whether resistance exercise training induces markers of mitochondrial content in elderly to a similar extent seems not clear.

In the present study, we therefore investigated the effect of resistance exercise training on strength and the protein expression or phosphorylation of factors important for upregulating (MyoD, myogenin, and IGF-I-R) and downregulating (activin receptor IIB (actRIIB) and smad2) skeletal muscle mass and mitochondrial markers in elderly compared to young individuals. In addition, we aimed at elucidating whether subsequent deconditioning affected these parameters in young and elderly similarly.

#### **2. Materials and Methods**

#### *2.1. Subjects*

Young and elderly volunteers were recruited with the criteria that for the elderly group age should be ≥74 years old and for the younger group age <30 years old. Exclusion criteria were non-sedentary status, illness requiring medical treatment other than treatment for hypertension and antithrombotic treatment, severe back or musculoskeletal pain, rheumatologic or neurological disorders, traumatic musculoskeletal and/or joint injuries, smoking, cardiovascular disease, attendance rate below 80% of total exercise sessions, additional exercise during the exercise phase, or failure to comply with instructions of inactivity during the deconditioning phase. Sedentary was defined as performing a maximum of three kilometers of cycling for transportation a day.

Twenty-two healthy, sedentary participants participated in the study; four were excluded due to noncompliance. Nine elderly, healthy persons—five men and four women (82 ± 7 year old)—fulfilled the inclusion criteria, and completed the resistance exercise training and deconditioning interventions. Data were compared to those found in nine young, healthy persons, also five men and four women (23 ± 3 yrs. of age). All participants completed a detailed medical history and had a normal neurological examination before entering the study. Demographic data of participants are shown in Table 1.


**Table 1.** General demographic data.

BMI, Body Mass Index; LBM, Lean Body Mass, LLM, lean leg mass. Age, height, weight, and BMI are presented at baseline pre intervention. Body fat, LBM, and LLM was measured before and after six weeks of resistance exercise training in elderly and young men and women. Data are shown as means ± SD. *n* = 9 in both groups. \*\*\* Significantly different (*p* < 0.001) from young group.

The study was approved by the Health Research Ethics Committee of the Capital Region of Copenhagen (No. KF-293615) and complied with the guidelines set out in the Declaration of Helsinki. The subjects were all informed about the nature and risks of the study and gave written consent to participate before inclusion.

#### *2.2. Study Design*

Nine young and 9 elderly participants completed a six-week resistance exercise training intervention of the lower body (two-legged knee extension) followed by eight weeks of deconditioning (Figure 1). Muscle strength was evaluated by a three-repetition max test before and after resistance exercise training. Skeletal muscle biopsies were taken from the vastus lateralis muscle before and after resistance exercise training and after two, four, six, and eight weeks of deconditioning for measurement of myogenic regulatory factors and mitochondrial markers. DEXA scanning of body composition was performed before and after resistance training.

#### *2.3. DEXA Scanning*

A whole-body Dual-Energy X-ray Absorptiometry (DEXA) scan (GE Medical Systems, Lunar, Prodigy, Chicago, IL, USA) was performed prior to the intervention and after the resistance exercise training intervention. The images were analyzed using enCORE™2004 Software (v.8.5) (GE Medical Systems). Reliability of this DEXA scanning was recently described [39].

#### *2.4. Exercise Equipment and Protocol*

Testing and exercise training intervention were carried out in a two-legged knee extension resistance exercise model using standard strength exercise equipment machines (Nordic Gym, Technogym, Cesena, Italy). Furthermore, to compensate for muscle imbalances during the selective exercise of the quadriceps, the exercise decline leg press (Nordic Gym) was incorporated into the exercise regimen.

**Figure 1.** Study design overview. Eighteen participants completed a six-week resistance exercise training intervention followed by eight weeks of deconditioning (detraining—no exercise). Muscle strength was evaluated by a three-repetition max test before and after resistance exercise training. Skeletal muscle biopsies were taken from the vastus lateralis muscle on each test day. Furthermore, a biopsy was taken after two, four, and six weeks of deconditioning.

#### *2.5. Strength Testing*

Strength testing was performed using a three-repetition maximum (RM) test-protocol. Before initial testing, participants were familiarized with the equipment and test protocol on a separate occasion to reduce the impact that skill learning has on strength performance. The estimated measure of bilateral knee extension muscle strength was recently found to be applicable for monitoring adaptations promoted by physical exercise for older adults with and without sarcopenia [40].

Three repetition maximum test (3RMT): Prior to the 3RMT, participants warmed up using five minutes of low intensity (60–80 watt and 30–50 watt for young and elderly, respectively) cycling ergometer exercise. Afterwards, participants were instructed to execute four repetitions in each attempt. Full range of motion (ROM) for three consecutive repetitions and failure to complete a 4th repetition across a full-ROM was set as a criterion for a successful 3RM estimate. Participants rested 3 min after warm-up, and 1.5 min between all other attempts. After 10 min of rest, the validity of the estimate was evaluated by trying to outperform the current 3RM estimate. 1RM was calculated using Brzycki's formula [41]. 3RMT was measured before and after the resistance training intervention (Figure 1).

#### *2.6. Resistance Exercise Training and Deconditioning Interventions*

The resistance exercise training intervention lasted for six weeks and consisted of 16 supervised resistance exercise sessions. Resistance exercise followed a progressive protocol in weekly exercise sessions from two to three sessions per week after the first two weeks of exercise. Sessions were divided into three sessions of different load carried on a two-legged knee extension and a decline leg press machine to voluntary failure, and each set was separated by three minutes of rest. The first session encompassed three sets of 10–12 repetitions with 10–12 RM load, followed by three sets of 6–8 repetitions with 6–8 RM load, ending with three sets of 4–6 repetitions with 4–6 RM load. Each session was separated by approximately 48 h of rest.

In addition to and following knee extension resistance exercise, participants exercised in the decline leg press with the same exercise protocol (e.g., three sets of 10–12 reps with 10–12 RM in both exercises in the same session). After six weeks of resistance exercise training, participants stopped the exercise program and returned to their habitual sedentary lifestyle and were instructed not to initiate any new form of exercise the following eight weeks. This was ensured by participants wearing accelerometers and weekly interviews of the participants.

#### *2.7. Skeletal Muscle Biopsy*

A skeletal muscle biopsy was performed in vastus lateralis right leg muscle before and after the six weeks resistance exercise training intervention, and after two, four, six, and eight weeks of deconditioning (post2w, post4w, post6w, and post8w) approximately one hour post the acute 3RMT on the experimental days. The biopsy was performed as previously described using a 5 mm percutaneous Bergström needle [42]. Needle entry was at least three centimeters away from the previous insertion to avoid scar tissue and interference with data due to post-biopsy edema, regeneration, and cellular infiltration. Muscle samples were immediately frozen in isopentane cooled by liquid nitrogen before storage at −80 ◦C for later analysis.

#### *2.8. Western Blotting Analysis*

Western blot analysis was performed as previously described [43]. Biopsies were sectioned on a cryostat at −20 ◦C and homogenized in ice-cold lysis buffer with protease and phosphatase inhibitors (10 mM Tris, pH 7.4, 0.1% Triton-X 100, 0.5% sodium deoxycholate, 0.07 U/mL aprotinin, 20 M leupeptin, 20 M pepstatin, 1 mM phenylmethanesulfonyl fluoride (PMSF), 1 mM EDTA, 1 mM EGTA, 1 mM DTT, 5 mM β-glycerophosphate, 1 mM sodium fluoride, 1.15 mM sodium molybdate, 2 mM sodium pyrophosphate decahydrate, 1 mM sodium orthovanadate, 4 mM sodium tartrate, 2 mM imidazole, 10 nM calyculin, and 5 mM cantharidin; Sigma-Aldrich, St. Louis, MO, USA) using a Bullet Blender bead-mill at 4 ◦C (Next Advance, Averill, NY, USA). The homogenate was directly centrifuged at 15,000× *g* for 5 min at 4 ◦C. The supernatant was immediately transferred to new Eppendorf tubes and added 4× sample buffer including beta mercapto-ethanol. Equal amounts of extracted muscle proteins (10 µL) were separated on 4–15% polyacrylamide gels (Bio-Rad, Hercules, CA, USA) at 200 V for 40–50 min along with molecular weight markers (Bio-Rad). Proteins were transferred to PVDF membranes at 2.5 A for 5 min using a Trans-Blot Turbo (Bio-Rad) and blocked in Bailey's Irish cream (R. J. Bailey & Co, Dublin, Ireland) for 30 min and washed in TBS-T to remove excess Bailey's (3 × 10 min). The study investigated the expression and/or phosphorylation of proteins involved in muscle development/regeneration (IGF-I-R, MyoD, myogenin) and negative regulators of muscle mass (actRIIB and smad2) as well as porin [44], a mitochondrial membrane protein, to assess any changes in mitochondrial content. Thus, to investigate MRFs, antibodies against MyoD (45 kDa; diluted 1:1000; host: mouse; Thermo Fisher Scientific, Waltham, MA, USA) and myogenin (F5D) (40/25 kDa; diluted 1:1000; host: mouse; Developmental Studies Hybridoma Bank (DSHB), University of Iowa, IA, USA) were used. Antibodies against phosphorylated insulin-like growth factor 1 receptor (p-IGF-IR beta Y1135/1136; 95 kDa; diluted 1:500; host: rabbit; Cell Signaling Technology, Danvers, MA, USA), activin IIB receptor (58 kDa; diluted 1:1000; host: rabbit; ab180185, Abcam, Cambridge, UK), and phospho-smad2/3 (pSer250; 58 kDa; diluted 1:1000; host rabbit; Cell Signaling Technology) were used to investigate if muscle growth regulation had changed. Antibodies against porin (30–33 kDa; diluted 1:50,000; host: mouse; Thermo Fisher Scientific) were used to investigate a marker of mitochondrial content.

Antibodies against glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were used at 1:5000 (ab22555; Abcam, Cambridge, UK) as loading control. Secondary goat anti-rabbit and goat anti-mouse antibodies coupled with horseradish peroxidase at concentration 1:10,000 were used to detect primary antibodies (DAKO, Glostrup, Denmark). Immunoreactive bands were detected by chemiluminescence using Clarity Max, (BioRad), quantified using a GBox XT16 darkroom, and GeneTools software was used to measure the intensities of immunoreactive bands (Syngene, Cambridge, UK). Immunoreactive band intensities were normalized to the intensity of the GAPDH bands for each subject to correct for differences in total muscle protein loaded on the gel.

#### *2.9. Muscle Histology and Immunohistochemistry*

Cryosections (10 µm) were cut from biopsies mounted in Tissue-Tek (Sakura Finetek Europe B.V., AJ Alphen aan den Rijn Netherlands), mounted on glass slides, and stored at −20 ◦C until stained. To assess myosin heavy chain (MHC) muscle fiber type distribution, sections were stained with MHC antibody clone BA-D5 (DSHB) for MHC type I, and a secondary goat anti-mouse antibody was used (GAM IgG2b Alexa Fluor 594, Thermo Fisher Scientific). For MHC type II assessment, sections were stained with MHC antibody clone A4.74 (DSHB), and a secondary goat anti-mouse antibody (GAM IgG1 Alexa Fluor 488) was used. All sections were observed at room temperature using a Nikon 20× Plan Apo VC N/A 0.75 mounted on a Nikon Ti-E epifluorescence microscope (Nikon Instruments, Melville, NY, USA). Images of the entire sections were acquired at 20× with a 5-Mpixel Andor Neo camera for fluorescence imaging (Andor, Belfast, Northern Ireland), using NIS-Elements Advanced Research (AR) software (Nikon Instruments) and merged in software.

#### *2.10. Mitochondrial Citrate Synthase Enzyme Activity*

Citrate synthase enzyme activity was investigated in muscle biopsies pre-exercise, post-exercise, and after 8 weeks of deconditioning. In short, skeletal muscle tissue (~200 mg) was sectioned on a cryostat (Microm HM550, Thermo Fisher, by, stat) at −20 ◦C and homogenized in ice-cold CelLytic MT (Mammalian tissue lysis/extraction reagent) containing protease inhibitor cocktail. The tissue was homogenized using a Bullet Blender bead-mill at 4 ◦C (Next Advance, Averill, NY, USA). The homogenate was directly centrifuged at 15,000× *g* for 5 min at 4 ◦C. The supernatant was transferred to new Eppendorf tubes and used for subsequent analysis. The assay was carried out according to the manufacturer's instructions (#CS0720, Sigma-Aldrich). Briefly, the assay solutions were heated at 25 ◦C. A master mix consisting of 1× assay buffer, 30 mM Acetyl-CoA solution, and 10 mM DTNB solution were mixed and added in the lysate to perform triple measurements per sample. Citrate synthase was measured by reading absorbance at 412 nm every 10th second for 1.5 min, and thereafter adding 10 mM OAA solution and then remeasured again every 10 s for 1.5 min at 412 nm.

#### *2.11. Statistical Analysis*

All statistical analyses were carried out using Excel 2010 (Microsoft®, Redmond, WA, USA) and GraphPad PRISM 8 (GraphPad, San Diego, CA, USA). A Shapiro–Wilkinson test was performed to test for normal distribution of data. Baseline subject characteristics were evaluated with unpaired *t*-tests between young and elderly groups and by a repeated measures two-way ANOVA for DEXA data before and after training (Table 1).The differences among groups were analyzed by a three-way repeated measures ANOVA in Figure 2A and a two-way repeated measures ANOVA in Figure 2B, Figure 3, and Table 2, followed by Tukey's multiple comparison tests when ANOVA revealed significant interactions. Prior to this, an additional two-way ANOVA was performed to ensure no gender differences prior to pooling data for male and females.). Correlation analyses were performed with the Pearson's product-moment correlation coefficient. All data are presented as means ± standard deviation (SD). Differences were considered to be statistically significant when *p* < 0.05.

**Figure 2.** Muscle strength and muscle fiber type composition. (**A**) Quadriceps muscle strength measured in a three repetition maximum test before and after six weeks of resistance exercise training in elderly and young men and women. (**B**) Pre-intervention muscle fiber type distribution shown as bar graph and by representative cross-sectional images of m. vastus lateralis in a younger and older woman showing fiber type distribution of myosin heavy chain (MHC) type I (red) and type II (green). \* *p* < 0.05, post-exercise vs. pre-exercise within the same group. # *p* < 0.05, pre-exercise, young men vs. young women. *n* = 5 elderly men, *n* = 4 elderly women, *n* = 5 young men, and *n* = 4 young women. All data are presented as means ± SD.


Porin protein content and maximal muscle citrate synthase (CS) activity measured pre-training, following six weeks of resistance exercise training (post training), and after eight weeks of subsequent deconditioning (post decondition). Porin protein content is expressed relative to young pre training. Data are shown as means ± SD. *n* = 9 in both groups.

**Figure 3.** Muscle regulatory factors. Muscle regulatory factors measured in skeletal muscle pre and post six weeks of resistance exercise training and during 2, 4, 6, and 8 weeks into a subsequent deconditioning period in young (red bars) and elderly (blue bars) individuals. (**A**) Protein expression of activin receptor IIB, (**B**). Phosphorylation level of smad2 at Ser245/250/255. (**C**) Protein expression of MyoD. (**D**) Protein expression of myogenin. (**E**) Phosphorylation level of IGF-I-R at Tyr1135 /1136. Measurements have been performed as single determinations by Western blotting. Representative Western blots are shown in Supplementary Figure S1. *n* = 9 in young group and *n* = 9 in the elderly group. Values are arbitrary units (means ± SD) and expressed relative to young group pre training. \* *p* < 0.05, young vs. elderly group, \*\* *p* < 0.01, main effect of age independently of training and deconditioning. ANOVA F-values (Ftime/Fage/Ftime×age): (**A**) 1.08/11.62/0.32; (**B**) 0.76/0.58/0.49; (**C**) 0.77/2.97/0.23; (**D**) 0.09/0.15/1.20; (**E**) 0.54/8.62/1.41.

#### **3. Results**

#### *3.1. Anthropometry*

Total body weight, body mass index (BMI), body fat %, and lean body mass % were similar between the young and the elderly group (Table 1). Six weeks of resistance exercise training did not lead to changes in whole body fat %, lean body mass %, or lean leg mass, as a read out for muscle mass, in the trained legs in neither the young nor the elderly individuals.

#### *3.2. Muscle Strength*

Six weeks of resistance exercise training increased quadriceps muscle strength in the elderly group by 78% (53.4 ± 14.3 kg (pre-exercise) vs. 95.0 ± 22.0 kg (post-exercise); *p* < 0.05), which was similar to that found in the young healthy persons (83.5%; 97.1 ± 27.5 kg (pre-exercise) vs. 178.2 ± 44.2 kg (post-exercise); *p* < 0.05) (Figure 2A). Pre-exercise, the elderly men did not have a significantly greater muscle strength compared to elderly women (56.2 ± 16.1 kg vs. 46.5 ± 2.5 kg), whereas a gender difference in muscle strength was observed in the younger group, in which the younger men had a 59% greater muscle strength at pre-training compared to younger women (119.2 ± 19.5 kg vs. 75 ± 12.6 kg; *p* < 0.05) (Figure 2A). No significant differences in strength between genders were observed post-exercise within the elderly or young group (Figure 2A).

#### *3.3. Muscle Fiber Type Composition*

No pre-exercise fiber type differences were seen between gender, young, and elderly participants (Figure 2B).

#### *3.4. Myogenic Regulatory Factors*

Six weeks of resistance exercise training and 8 weeks of deconditioning did not change the protein expression of MyoD, actRIIB, and myogenin and phosphorylation of Smad2 and IGF-I- receptor in the elderly and the young group (Figure 3A–E).

MyoD protein expression were overall higher (*p* < 0.01) in muscles of elderly compared with young individuals (Figure 3A).

No differences in total protein expression of actRIIB and myogenin and phosphorylation of Smad2 and IGF-I-R were observed pre-training or after six weeks following resistance training in young versus elderly participants (Figure 3B–E). IGF-I receptor phosphorylation at Tyr1135 /1136 was lower in the younger group of healthy persons compared to the elderly group two weeks post-exercise (post2w) (0.7 ± 0.5 vs. 1.9 ± 1.1, *p* < 0.05), four weeks post-exercise (post4w) (0.6 ± 0.9 vs. 1.4 ± 1.1, *p* < 0.05) and six weeks post-exercise (post6w) (0.6 ± 0.7 vs. 2.6 ± 2.7, *p* < 0.05) (Figure 3E). There was no difference between genders at all time points in both groups in all protein and phosphorylation levels investigated, why these data were pooled in the data shown.

#### *3.5. Mitochondrial Markers: Porin and Citrate Synthase*

The protein expression of porin did not change with six weeks of resistance exercise training and remained unchanged after deconditioning in both the young and the elderly and was not significantly different between the groups (Table 2).

The maximal muscle enzyme activity of citrate synthase in the elderly was not significantly different from that found in the young participants (Table 2). Maximal muscle enzyme activity of citrate synthase in the elderly group remained unchanged with resistance exercise training and subsequent deconditioning, which was similar to that found in the young group (Table 2). There was no difference in the citrate synthase activity among genders in the elderly and young groups, which is why these data were pooled (Table 2).

#### *3.6. Correlation between Myogenic and Mitochondrial Factors and Muscle Strength*

There was no association between any of the studied MRFs (MyoD, myogenin, actRIIB protein expression, and IGF-I-R and smad2 phosphorylation) or mitochondrial factors (citrate synthase activity and porin protein expression) and absolute or relative change in muscle strength after six weeks of resistance exercise training in the elderly or the young group.

#### **4. Discussion**

Resistance exercise training and deconditioning offer a unique opportunity to investigate differences in myogenic regulatory factors that may be crucial in the age-related loss of muscle mass and strength. The aim of this study was to investigate regulation of myogenic factors prior and in response to resistance exercise training and deconditioning in elderly (74–92 years of age) versus young, healthy, gender-matched individuals. The primary findings were (1) six weeks of intensive resistance exercise training induced the same increase in muscle strength in young and older individuals, (2) the key myogenic regulating factors (MyoD, myogenin, and IGF-I-R) were similar in muscles of young and elderly individuals and not differently regulated by six weeks of resistance exercise training or subsequent eight weeks of deconditioning, and (3) no change was found in markers of oxidative capacity and mitochondrial content after six weeks of resistance exercise training in either elderly or young healthy persons.

Age-related loss of muscle strength is inevitable and cannot be explained by age-related decreased physical activity level alone [45]. It has been suggested that elderly persons have a blunted muscle hypertrophy response to resistance exercise training [17–19]. Thus, it could be that differences in muscle mass and function between young and elderly are driven by age-related changes in the ability to gain and/or maintain muscle strength with age. However, the present study showed that six weeks of intensive resistance exercise training resulted in the same increase in quadriceps muscle strength in elderly compared to that found in young, gender-matched, sedentary individuals. Therefore, skeletal muscle of elderly has the same capacity to increase strength in response to resistance training as in young healthy individuals. This finding is important in a translational perspective, emphasizing that resistance exercise training benefits elderly as much as in young persons and therefore seems to be a valid tool to combat loss of muscle function and strength in aging.

Myogenic regulatory factors promote and regulate the expression of muscle-specific genes after muscle injury or strenuous resistance exercise leading to muscle hypertrophy [46]. It has been hypothesized that the inevitably age-related muscle strength loss may relate to downregulation of MRFs, and thus skeletal muscle atrophy, which we were unable to corroborate. With the same levels of MRFs in elderly compared to young persons in the present study, our findings contrast the majority of previous studies measuring on mRNA levels. Previous studies found elevated levels of MyoD, myogenin, and IGF-I-R mRNA in elderly both at rest [17,31–34] and in response to exercise training compared to younger individuals [17,47–50]. This suggests that the increase in MRF mRNA levels represented a continuous compensatory mechanism to preserve muscle protein and mass with aging [17]. The present study is the first to investigate protein levels of MRFs, obviating the issues with changes in mRNA levels that may not translate into similar changes in protein expression due to post-translational regulation [51]. The present study suggests that the myogenic program is intact in the elderly, as the levels of MyoD, myogenin, and IGF-I-R are activated to the same extent as in younger skeletal muscle. An overall higher level of MyoD protein expression in the elderly compared with the young muscle, and a higher IGF-I-R phosphorylation 2, 4, and 6 weeks into the deconditioning period in the elderly compared with young individuals support that compensatory mechanisms in MRF regulation contribute to preserve muscle protein and mass in aging. Importantly, our study underscores that protein and phosphorylation levels should be measured in favor of mRNA. Our finding further suggests that an intact anabolic muscle response seems able to compensate in part for the loss of muscle.

As the expression of MRFs are time-dependent in relation to external and internal stimuli, it could be hypothesized that lack of differences in MRFs in the present versus other studies (measuring mRNA levels though) investigating this could be related to the timing of the muscle biopsy sampling. In the present study, the muscle biopsy intervention was taken one hour post-exercise. As the expression of the proteins that was investigated in the present study is expected to be stable and not affected by an acute bout of exercise, timing of muscle sample seems not have an impact on the data presented in the present study. This is supported by findings in post-exercise muscle biopsy intervention (3 h post-exercise), in which no increase was found in key myogenic factors (MyoD, myf-6), except for

myogenin [52], underscoring that timing of muscle biopsy sampling likely did not impact the protein levels of MRFs in the present study.

Muscle growth is tightly regulated through the myostatin, actRIIB, and smad2 pathway [53]. In response to muscle disuse, this and other pathways mediate a decrease in muscle mass [54]. In line with this, studies have shown that inhibition of myostatin-actRIIB-smad pathway leads to skeletal muscle hypertrophy in mice [55]. Studies by Hulmi et al. [35,36] have indicated that factors downregulating muscle mass in aged muscle could be attenuated in response to resistance exercise, as the mRNA level of actRIIB was downregulated after 21 weeks of resistance exercise in elderly (62.3 ± 6.3 years of age). The findings from that study indicate that proteins responsible for negative muscle mass regulation, e.g., actRIIB and smad2, could be upregulated in inactive aged muscle, resulting in decreased muscle mass and thus strength. However, our results did not support that finding. Instead, our data demonstrate that skeletal muscles of elderly have the same dynamics of MRF-mediated hypo- and hypertrophy, indicating that resistance exercise and deconditioning regulatory effects on skeletal muscle anabolism is the same irrespective of age.

Citrate synthase is a key mitochondrial matrix enzyme and a strong indicator of oxidative capacity in skeletal muscle [56–59] and maximal citrate synthase activity was also found to strongly correlate with mitochondrial volume measured by electron microscopy in skeletal muscles of healthy, young men [58]. Porin (also known as voltage dependent anion channel, VDAC1) is a pore-forming protein localized in the outer membrane of mitochondria, and is used as a marker of mitochondrial content [60,61]. Alterations in mitochondrial function and content has been proposed to be a factor underlying sarcopenia and muscle atrophy [62,63]. In order to investigate whether age-related decline in muscle strength was accompanied by muscle mitochondrial impairments in response to resistance training, muscle citrate synthase activity, and porin protein expression were measured before and after six weeks of resistance exercise training and eight weeks of deconditioning. Data showed that there was no change in oxidative capacity and indices of mitochondrial content after six weeks of resistance exercise training in either elderly or young healthy individuals, indicating that the gain in muscle strength was not associated with any changes in mitochondrial content.

It has been hypothesized that change in age-related muscle mass is driven by loss of muscle fiber type II number with age. However, findings regarding age-related changes in muscle fiber type II number have been ambiguous [64–67]. In the present study, the elderly individuals were older than those previously studied (+74 years old), and despite an age difference of 60 years between the young and elderly participants, there was no difference in number of type I and II fibers between elderly and younger persons. In the present study, we did not measure fiber type composition after training and deconditioning. Fiber type composition is in most studies not changed with exercise training [68] especially not within 6 weeks of resistance training. However, we cannot exclude that fiber type composition was mildly affected by exercise training in the present study. Furthermore, it was not within the scope of the present investigation to evaluate fiber size changes with resistance exercise training and deconditioning and it remains to be established, whether muscle fiber sizes are affected by 6 weeks of resistance training and subsequent 8 weeks of deconditioning in skeletal muscle of young and elderly.

#### **5. Conclusions**

Despite the fact that aging is associated with substantial loss of muscle mass resulting in a net loss of muscle strength and function, our study showed that elderly (aged 74+ years old) are remarkably capable of gaining muscle strength compared to younger participants in response to resistance exercise training. This underlines the applicability of resistance exercise training as an important instrument to diminish age-related loss of muscle function. Interestingly, the preserved ability to gain muscle strength with resistance exercise training was associated with a similar interaction between myogenic factors for up- and downregulation of skeletal muscle in elderly and young individuals. Thus, our data

suggests that the entire myogenic regulatory program is not impaired in aged relative to younger skeletal muscle.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/7/2188/s1, Figure S1: Representative Western blots.

**Author Contributions:** Conceptualization, F.D.T and T.D.J.; methodology, T.K., K.A.N.Q.; formal analysis, K.A.N.Q., A.M.F.; investigation, A.M.F., F.D.T., K.A.N.Q., T.K., M.-L.S., T.D.J.; resources, J.V.; data curation, A.M.F., F.D.T., K.A.N.Q.; writing—original draft preparation, A.M.F., K.A.N.Q., T.D.J.; writing—review and editing A.M.F., F.D.T., K.A.N.Q., T.K., M.-L.S., J.V., T.D.J.; visualization, A.M.F., K.A.N.Q., T.D.J.; supervision, T..K., J.V., T.D.J.; project administration, F.D.T., T.D.J.; funding acquisition, J.V. All authors have read and agree to the published version of the manuscript.

**Funding:** A.M.F. was supported by a research grant from the Danish Diabetes Academy (grant number NNF17SA0031406), which was funded by the Novo Nordisk Foundation. A.M.F. was further supported by the Alfred Benzon Foundation.

**Acknowledgments:** We thank Tessa Munkeboe Hornsyld and Danuta Goralska-Olsen for excellent technical assistance.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **Comparison of Three Nutritional Screening Tools with the New Glim Criteria for Malnutrition and Association with Sarcopenia in Hospitalized Older Patients**

**Francesco Bellanti 1,\* , Aurelio Lo Buglio <sup>1</sup> , Stefano Quiete <sup>1</sup> , Giuseppe Pellegrino <sup>1</sup> , Michał Dobrakowski <sup>2</sup> , Aleksandra Kasperczyk <sup>2</sup> , Sławomir Kasperczyk <sup>2</sup> and Gianluigi Vendemiale <sup>1</sup>**


Received: 25 May 2020; Accepted: 16 June 2020; Published: 17 June 2020

**Abstract:** The integrated assessment of nutritional status and presence of sarcopenia would help improve clinical outcomes of in-hospital aged patients. We compared three common nutritional screening tools with the new Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria among hospitalized older patients. To this, 152 older patients were assessed consecutively at hospital admission by the Malnutrition Universal Screening Tool (MUST), the Subjective Global Assessment (SGA), and the Nutritional Risk Screening 2002 (NRS-2002). A 46% prevalence of malnutrition was reported according to GLIM. Sensitivity was 64%, 96% and 47%, and specificity was 82%, 15% and 76% with the MUST, SGA, and NRS-2002, respectively. The concordance with GLIM criteria was 89%, 53% and 62% for the MUST, SGA, and NRS-2002, respectively. All the screening tools had a moderate value to diagnose malnutrition. Moreover, patients at high nutritional risk by MUST were more likely to present with sarcopenia than those at low risk (OR 2.5, CI 1.3-3.6). To conclude, MUST is better than SGA and NRS-2002 at detecting malnutrition in hospitalized older patients diagnosed by the new GLIM criteria. Furthermore, hospitalized older patients at high risk of malnutrition according to MUST are at high risk of presenting with sarcopenia. Nutritional status should be determined by MUST in older patients at hospital admission, followed by both GLIM and the European Working Group on Sarcopenia in Older People (EWGSOP2) assessment.

**Keywords:** nutritional status; sarcopenia; nutritional screening tools; hospitalized older patients

#### **1. Introduction**

The average population age is increasing in developed countries, causing a rise in older subjects with consequently greater need of hospitalization [1]. In such scenario, the association between hospitalization and malnutrition is increasingly reported, with a negative impact on treatment response, functional recovery, hospital length-of-stay and costs, and quality of life [2,3]. Hospitalization is also linked to loss of muscle mass and strength, which define sarcopenia [4]. Malnutrition is strongly associated with sarcopenia, and the presence of both conditions is related to several adverse outcomes [5]. The concomitant occurrence of malnutrition and sarcopenia is defined as malnutrition-sarcopenia

syndrome (MSS), which represents a prognostic factor for hospitalized older adults [6]. The integrated assessment of nutritional status and presence of sarcopenia would help improve clinical outcomes of such patients.

Diagnosis of malnutrition or risk of malnutrition requires a comprehensive nutritional assessment, which is frequently difficult to perform on all in-hospital patients due to both time and financial restraints [7]. To overcome this limitation, the Global Leadership Initiative on Malnutrition (GLIM) recommends a two-step model in which diagnosis assessment is preceded by risk screening using any validated tool [8]. Nevertheless, despite several tools for rapid identification of malnutrition in older adults [9], patients are not consistently screened for nutritional status at hospital admission [10,11].

The Mini Nutritional Assessment (MNA) is considered one of the most validated tools for the identification of malnutrition or risk of malnutrition, and it is particularly used in older people [12–14]. However, the MNA has disadvantages such as subjective questions unsuitable to hospitalized older people, inability to be used in patients with cognitive impairment, and 10 to 15 min to be performed [7,15]. Several nutritional screening tools have been applied to rapidly identify malnutrition in older patients in hospital settings, and each present with improvements and weaknesses [7]. Very recently, a systematic review evaluated the available studies which considered malnutrition and sarcopenia simultaneously, resulting in methodological unpredictability [16].

First, this study aimed to compare different tools for nutritional screening, such as the Malnutrition Universal Screening Tool (MUST), the Subjective Global Assessment (SGA), and the Nutritional Risk Screening 2002 (NRS-2002) in hospitalized older patients, in order to define their sensitivity, specificity, and rapidity with respect to the GLIM consensus, chosen as the reference method. Furthermore, the present investigation evaluated the association between the alteration of nutritional status identified by these tools and the presence of sarcopenia.

#### **2. Experimental Section**

#### *2.1. Study Design and Participants*

We collected and analyzed data from older patients hospitalized at the Internal and Aging Medicine clinic of the "Ospedali Riuniti", a teaching hospital in Foggia (Italy). We recruited consecutive patients aged 65 years or older, admitted to our ward from March 2019 to February 2020. Frequency of the main causes for hospital admission is reported in Table 1. The exclusion criteria were the following: dysphagia, active cancer, severe cognitive impairment (assessed with a Mini Mental State Examination score ≤ 9 points), inability to comply with the study protocol or to provide written informed consent. Further exclusion criteria were chronic bedridden conditions, physical handicap, severe neuromuscular disease, and use of drugs affecting body composition (such as glucocorticoids, statins, active vitamin D metabolites, anabolic steroids, selective estrogen receptor modulators). The study was approved by our Institutional Review Board at the Ospedali Riuniti in Foggia and performed according to the Declaration of Helsinki. All patients gave written informed consent.

#### *2.2. Biochemical Analysis, Anthropometric Measurements and Body Composition Evaluation*

A blood sample was taken at the time of admission for the determination of hemoglobin (Hb) and lymphocytes in whole blood, and total proteins, albumin, total cholesterol, and iron in the serum. Height, body weight, and waist, arm, and hip circumference, as well as tricipital, bicipital, subscapular, and supra-iliac skinfold thicknesses were measured according to standardized procedures. Body mass index (BMI) was calculated as the ratio between weight in kilograms and the square of height in meters. Body composition was assessed within 24 h from admission by bioelectrical impedance using a BIA 101-F device (Akern/RJL, Florence, Italy), as previously reported [17]. The BIA analyzer underwent calibration by the manufacturer, and the measurements were validated according to previously published equations [18].


**Table 1.** Baseline demographic, clinical, anthropometric, and biochemical characteristics of patients, stratified according to the Global Leadership Initiative on Malnutrition consensus.

Data are expressed as mean ± SD (continuous variables) or frequency and percentage (categorical variables). Statistical differences were assessed by Student's *t*-test (continuous variables) or by Pearson's Chi-squared test and Fisher's exact test (categorical variables). M, male; F, female; MMSE, Mini-Mental State Examination. Bold: statistically significant.

#### *2.3. Tools for Screening of Nutritional Status*

The MUST, SGA, and NRS-2002 tools were used for nutritional screening, and the time (in seconds) required to complete each test was recorded. To avoid any interindividual variance, all tools were performed by an experienced operator.

The MUST includes three clinical parameters and rates each parameter as 0, 1 or 2 as follows: (a) BMI > 20 kg/m<sup>2</sup> = 0; 18.5–20.0 kg/m<sup>2</sup> = 1; <18.5 kg/m<sup>2</sup> = 2; (b) weight loss in the past 3–6 months < 5% = 0; 5–10% = 1; >10% = 2; (c) acute disease: absent = 0; if present = 2. Overall risk of malnutrition is established as follows: 0 = low risk; 1 = medium risk; 2 = high risk [19].

The SGA questionnaire includes patient history (weight loss, changes in dietary intake, gastrointestinal symptoms and functional capacity), physical examination (muscle, subcutaneous fat, sacral and ankle edema, ascites) and the clinician's overall judgment of the patient status ((a) well nourished; (b) suspected malnourished or moderately malnourished; (c) severely malnourished) [20].

The NRS-2002 consists of a nutritional score and a severity of disease score and an age adjustment for patients aged > 70 years (+1). Nutritional score: weight loss 45% in 3 months or food intake below 50–75% in the preceding week = 1; weight loss 45% in 2 months or BMI 18.5–20.5 kg/m<sup>2</sup> and impaired general condition or food intake 25–60% in the preceding week = 2; weight loss 45% in 1 months or >15% in 3 months or BMI < 18.5 kg/m<sup>2</sup> and impaired general condition or food intake 0–25% in the preceding week = 3. Severity of disease score: hip fracture, chronic patients with acute complications = 1; major abdominal surgery, stroke, severe pneumonia, hematological malignancies = 2; head injury, bone marrow transplantation, intensive care patients with APACHE > 10 = 3. NRS-2002 score is the total of the nutritional score, severity of disease score and age adjustment. Patients are classified at no risk = 0, low risk = 0–1, medium risk = 3–4, and high risk = ≥ 5 [21].

#### *2.4. Diagnostic Criteria for Malnutrition and Sarcopenia*

Following the new GLIM diagnostic criteria, malnutrition was diagnosed when the patients met 1 phenotypic criterion (among non-volitional weight loss, low body mass index, and reduced muscle mass) and 1 etiologic criterion (among reduced food intake or assimilation, and disease burden/inflammatory condition), according to Table 2 [8].

**Table 2.** Bioelectrical impedance analysis parameters in patients stratified according to the Global Leadership Initiative on Malnutrition consensus.


Data are expressed as mean±SD. Statistical differences were assessed by Student's *t*-test. Bold: statistically significant.

Sarcopenia was diagnosed on admission according to the European Working Group on Sarcopenia in Older People updated recommendation (EWGSOP2) [22]. Particularly, sarcopenia was first assessed by gait speed or grip strength, and then, confirmed in subjects presenting with a relative skeletal muscle index (RSMI) < 7.25 kg/m<sup>2</sup> (men) or <5.67 kg/m<sup>2</sup> (women).

#### *2.5. Statistical Analysis*

Data were expressed as mean ± standard deviation of the mean (SDM) for quantitative variables, and as count and percentages for qualitative values. Gaussian distribution of the samples was evaluated by the Kolgomorov–Smirnov test. The significance of differences between 2 groups was assessed by Student's *t*-test (continuous variables) or in contingency tables by Pearson's Chi-squared test and Fisher's exact test (categorical variables). The significance of differences between more than 2 groups was assessed by the one-way analysis of variance (ANOVA) after ascertaining normality by the Kolgomorov–Smirnov test; Tukey–Kramer was applied as post hoc test. To determine the diagnostic concordance between the three screening tools and the GLIM diagnostic criteria for malnutrition, Cohen's statistic was calculated. The coefficient reflects the consistency of qualitative variables: = 1 indicates complete consistency between the variables, and = 0 indicates no consistency among the variables. Positive likelihood ratios and negative likelihood ratios were calculated for all three tools. Sensitivity and specificity values for the three nutritional screening tools with the GLIM diagnostic criteria for malnutrition were calculated. To determine the diagnostic concordance, consistency, accuracy, likelihood ratio, sensitivity, and specificity, medium and high-risk categories for the three nutritional assessment tools were combined, according to previous publications [23,24]. Receiver operating characteristic (ROC) curves of the three screening tools were also used to evaluate the ability to accurately distinguish malnourished patients. The Youden Index was calculated as (sensitivity + specificity) − 1 for each cut-off point. The odds ratio (OR) and the 95% confidence interval (CI) were calculated. Univariate binary logistic regression analysis was used to analyze the association between nutritional status and the presence of sarcopenia.

All tests were 2-sided, and *p* values <0.05 were considered statistically significant. Statistical analysis was performed with the Statistical Package for Social Sciences version 23.0 (SPSS, Inc., Chicago, IL, USA) and the package GraphPad Prism 6.0 for Windows (GraphPad Software, Inc., San Diego, CA, USA).

#### **3. Results**

#### *3.1. Patients Characteristics*

In total, 689 consecutive patients were evaluated for enrolment; of these, 152 met the inclusion criteria and did not present any of the exclusion criteria. According to the GLIM criteria, malnutrition was diagnosed in 70 patients (46%) at admission (Figure 1, Supplementary Table S3).

−

**Figure 1.** Participant flowchart. Other exclusion criteria were chronic bedridden conditions, physical handicap, severe neuromuscular disease, and use of drugs affecting body composition (such as glucocorticoids, statins, active vitamin D metabolites, anabolic steroids, selective estrogen receptor modulators). Diagnosis of malnutrition was performed according to the new criteria of the Global Leadership Initiative on Malnutrition.

Baseline demographic, clinical, anthropometric, and biochemical characteristics of patients presenting with malnutrition or not malnourished are represented in Table 1. Of note, we reported lower weight, arm and waist circumference, waist-to-hip ratio, bicipital, subscapular and supra-iliac skinfold thickness, serum total proteins, serum albumin, serum total cholesterol and blood hemoglobin in the group of patients with malnutrition with respect to the group with no malnutrition.

Interestingly, significant differences in body composition parameters were observed between the two groups (Table 2). In detail, patients with malnutrition were observed with reduced Body Cell Mass, Fat-Free Mass, Skeletal Muscle Index and Appendicular Skeletal Muscle Mass, and increased Total Body Water, Extracellular Water and Fat Mass as compared with not malnourished patients.

#### *3.2. Rapidity, Sensitivity, Specificity, Accuracy, and Diagnostic Value of Nutritional Screening Tools*

All patients were subjected to three nutritional screening tools (MUST, SGA, and NRS-2002) at admission. As shown in Figure 2, MUST was the less rapid tool as compared to SGA and NRS-2002.

The MUST misclassified 18%, the SGA 47%, and the NRS-2002 38% of patients. Sensitivity was 64.3% with the MUST, 95.7% with the SGA, and 47.1% with the NRS-2002, while specificity was 81.7%, 14.6% and 75.6% with the MUST, SGA and NRS-2002, respectively; MUST accuracy was 73.7%, while accuracy resulted 52% for SGA and 62.5% for NRS-2002 (Table 3).

Finally, the area under the curve (AUC) calculated by the ROC indicated that all three screening tools had a moderate value to diagnose malnutrition in hospitalized older patient (AUC of MUST, SGA, and NRS-2002 were found to be 0.80, 0.77 and 0.69, respectively; Figure 3). The highest Youden indexes were 0.461 for a MUST score ≥ 0.5 (sensitivity 0.643, specificity 0.818), 0.461 for a SGA score ≥ 8.5 (sensitivity 0.643, specificity 0.818), and 0.257 for a NRS-2002 score ≥ 2.5 (sensitivity 0.464, specificity 0.758).

**Figure 2.** Duration of the nutritional screening tools (time expressed in seconds), performed in all the 152 hospitalized patients enrolled in this study. Data are expressed as mean ± SD. Statistical differences were assessed by one-way ANOVA and Tukey as post hoc test. MUST, Malnutrition Universal Screening Tool; SGA, Subjective Global Assessment; NRS-2002, Nutritional Risk Screening 2002. \*\*\*\*: *p* < 0.0001 vs. MUST. ≥ ≥ ≥

**Figure 3.** Receiver Operating Characteristic (ROC) curve for prediction of malnutrition based on the score obtained by the Malnutrition Universal Screening Tool (MUST, blue line), the Subjective Global Assessment (SGA, green line), and the Nutritional Risk Screening 2002 (NRS-2002, yellow line).

#### *3.3. Malnutrition and Sarcopenia*

Χ According to the EWGSOP2 recommendation, sarcopenia was diagnosed in 77 (50.6%) patients; of these, 45 (64.3%) were also diagnosed with malnutrition according to the GLIM criteria, and 32 (39.0%) were not malnourished (X<sup>2</sup> = 9.641, *p* = 0.0019). We did not find any difference between genders with respect to the diagnosis of sarcopenia. Malnutrition diagnosed according to the GLIM criteria increased the risk of presenting with sarcopenia 2.7-fold (95% CI 1.4–4.9, *p* = 0.0029). There was a significant association between sarcopenia and nutritional status at high risk of malnutrition detected by MUST, but not by other nutritional screening tools (Table 4).



**Table 3.**Statistical comparison of nutritional diagnosis and screening tools values at hospital admission.

 Malnutrition Universal Screening Tool (MUST), Subjective Global Assessment (SGA) and Nutritional Risk Screening 2002 (NRS-2002) versus Global Leadership Initiative on Malnutrition(GLIM) criteria. CI, confidence interval; statistic, percent of agreement.


**Table 4.** Association between nutritional status and presence of sarcopenia on admission.

Incidence and odds ratio (OR; 95% confidence interval, CI), adjusted for age, gender, and education, between Global Leadership Initiative on Malnutrition (GLIM) diagnosis of malnutrition or nutritional screening tools and presence of sarcopenia. MUST, Malnutrition Universal Screening Tool; SGA, Subjective Global Assessment; NRS-2002, Nutritional Risk Screening 2002. Bold: statistically significant.

#### **4. Discussion**

This is the first study which compared the diagnostic reliability of different nutritional screening tools to the GLIM criteria in a population of hospitalized older patients. According to the GLIM framework, 46% of patients were identified as malnourished when using combinations of two criteria. This prevalence could be apparently high as compared with previous studies which used the GLIM criteria for the diagnosis of malnutrition [5,25–27]. Nevertheless, this investigation focused on a special population that presented with a high prevalence of etiologic GLIM criteria for malnutrition. Indeed, the prevalence of malnutrition is close to 50% when diagnosed in critically ill patients [28]. Furthermore, even though this study was not designed to validate the diagnosis of malnutrition in hospitalized older subjects according to the GLIM consensus, our data show that patients with malnutrition presented with alterations in anthropometry, biochemical parameters, and bioelectrical impedance analysis results, compatible with their impaired nutritional status.

Nutritional screening tools detect features associated with alterations of nutritional status to distinguish persons presenting with risk of malnutrition. These tools play an important role in providing a standardized and systematic approach to identifying malnutrition [29]. Considering the utility of such tools in a daily routine, they should be easy to use, rapid, sensitive, and specific, to be included in a defined clinical protocol [30]. In this study, we compared the MUST, created to identify malnutrition in care settings [31]; the SGA, considered by several Authors as the most validated tool in hospital settings [25]; the NRS-2002, a tool used in hospital settings to detect patients who would benefit from nutritional therapy [21]. We first considered the rapidity of each tool in our special population, concluding that the MUST requires longer time with respect to both SGA and NRS-2002. Medium and high nutritional risk was 39.5% by MUST, 90.1% by SGA, and 34.9% by NRS-2002, compared to 46% of patients being malnourished by GLIM consensus. Concordance of the three screening tools with respect to GLIM criteria resulted dissimilar. These data are similar to other comparisons between different nutritional screening tools applied to hospitalized older patients [32]. Overall, the three screening tools misclassified 11–47% of patients, the MUST having the highest concordance with GLIM framework compared with SGA and NRS-2002. Furthermore, the MUST showed higher specificity than SGA and NRS-2002, meaning that more hospitalized older patients presenting with no malnutrition were correctly identified as at a low risk of malnutrition than malnourished patients being at high risk. On the contrary, the SGA showed higher sensitivity with respect to MUST and NRS-2002, properly identifying hospitalized older patients with malnutrition as at high risk than well-nourished ones at low risk. A previous study analyzed the validity of GLIM criteria with respect to SGA, describing a higher sensitivity when weight loss was combined with high C-reactive protein values, and a higher

specificity with the combination of a low BMI and low food intake [25]. Both reduced food intake and increased C-reactive protein were registered very frequently in our population of hospitalized older patients, however, weight loss was more prevalent than low BMI, partially explaining the high sensitivity (but low specificity) of SGA. Finally, even though the ROC curve showed a moderate value to identify malnutrition by all three nutritional screening tools, MUST was found to have the greatest AUC with respect to SGA and NRS-2002. Based on the results of this study, the time spared in the administration of SGA or NRS-2002 is not well matched with accuracy or diagnostic value of these tools in hospitalized older patients. Further investigations are needed to confirm this observation.

This study reported a significant prevalence of sarcopenia diagnosed with the EWGSOP2 criteria, with malnutrition diagnosed with the GLIM criteria (64.3%). Malnutrition is considered as a determinant factor for the onset of sarcopenia, and the presence of malnutrition-sarcopenia syndrome (MSS) is associated with a four times higher risk of mortality in hospitalized older patients [6]. A recent longitudinal study investigated the incidence of sarcopenia (identified through the EWGSOP2 criteria) during a four-year follow-up in community-dwelling older individuals diagnosed with malnutrition at baseline according to both the European Society of Clinical Nutrition and Metabolism (ESPEN) and the GLIM criteria [5]. This report registered a threefold higher risk of developing sarcopenia in malnourished patients based on the GLIM [5]. Even though the present investigation is not designed as a prospective longitudinal study, our analysis shows that the risk of MSS is almost threefold in hospitalized older patients presenting with malnutrition at admission. Moreover, amongst the three screening tools applied, MUST is the only to identify older hospitalized patients at high risk of malnutrition with a significant 2.5 times higher risk of having MSS.

The strengths of this study consist in the use of standardized diagnostic criteria for the diagnosis of malnutrition or sarcopenia, and a rigorous statistical analysis. Nevertheless, this study presents several main limitations. First, it is a single center study with a small sample size, which restricted the subgroup analysis. Moreover, this study did not investigate the association between nutritional status and the underlying disease that led to hospitalization. The three nutritional screening tools were not compared with MNA, because of biased questions inappropriate to hospitalized older people even with mild or moderate cognitive impairment, and longer time to be performed. Muscle mass was evaluated by bioelectrical impedance, which could be influenced by fluid distribution changes. A further limitation of the study is that information about the dietary regimens or the pharmacological treatments potentially affecting the nutritional status of single participants was not registered. Moreover, in our study, we did not estimate other confounding factors, such as socioeconomic and family status, which could partially impact the results.

In conclusion, the present study reports a prevalence of malnutrition of 46% in hospitalized older patients, according to the GLIM framework criteria. The comparison of three different nutritional screening tools indicates that MUST is better at detecting malnutrition in hospitalized older patients diagnosed by the new GLIM criteria despite being less rapid, with respect to SGA and NRS-2002. Furthermore, there is a significant association between the presence of sarcopenia in hospitalized older patients at high risk of malnutrition according to MUST. This evidence confirms the importance of routine nutritional assessment in hospitalized older patients. We suggest that nutritional status should be determined by MUST in older patients at hospital admission, followed by both GLIM and EWGSOP2 assessment. The choice of this diagnostic tool could allow on-time nutritional intervention, thus preventing the worsening of negative caloric balance and loss of muscle mass. Furthermore, an early and valuable recognition of malnutrition and sarcopenia would be beneficial to plan individualized treatment during hospitalization and at discharge.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/6/1898/s1, Table S1: Main causes for hospital admission in patients stratified according to the Global Leadership Initiative on Malnutrition consensus. Table S2: Assessment criteria of malnutrition according to the Global Leader Initiative on Malnutrition (GLIM). Table S3: Prevalence of criteria of the Global Leader Initiative on Malnutrition (GLIM) registered in the study population.

**Author Contributions:** Conceptualization, F.B. and A.L.B.; methodology, F.B.; validation, F.B., A.L.B., S.Q., and G.P.; formal analysis, F.B., M.D., A.K. and S.K.; investigation, F.B., A.L.B., S.Q., G.P., M.D., A.K., and S.K.; resources, G.V.; data curation, F.B. and G.V.; writing—original draft preparation, F.B.; writing—review and editing, A.L.B., M.D., A.K., S.K. and G.V.; supervision, S.K. and G.V.; project administration, F.B. and G.V. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Acknowledgments:** Authors are grateful to Martina Valentino, Debora Testa and Emma Finamore for their technical assistance and support.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **E**ff**ects of Physical Exercises and Verbal Stimulation on the Functional E**ffi**ciency and Use of Free Time in an Older Population under Institutional Care: A Randomized Controlled Trial**

**Agnieszka Wi´sniowska-Szurlej 1,\* , Agnieszka Cwirlej-Soza ´nska ´ <sup>1</sup> , Natalia Wołoszyn <sup>1</sup> , Bernard Soza ´nski <sup>1</sup> and Anna Wilmowska-Pietruszy ´nska <sup>2</sup>**


**\*** Correspondence: wisniowska@vp.pl; Tel.: +48-604181162

Received: 18 January 2020; Accepted: 6 February 2020; Published: 9 February 2020

**Abstract:** Older people in institutional care are, for the most part, physically inactive and do not interact with each other or medical staff. Therefore, reducing sedentary behaviour is a new, important, and modifiable lifestyle variable that can improve the health of elderly people. The aim of the project was to assess the degree of improvement in functional performance and the possibility of changing habitual, free time behaviour among elderly people under institutional care by applying physical training with verbal stimulation. The study covered older people, aged 65–85 years, who are living a sedentary lifestyle in care homes in Southeastern Poland. Those who met the eligibility criteria were enrolled in the study and were assigned, at random, to one of four parallel groups: basic exercises (*n* = 51), basic exercises combined with verbal stimulation (*n* = 51), functional exercise training (*n* = 51), and functional exercise training with verbal stimulation (*n* = 51). No statistically significant differences in baseline characteristics were observed across the groups. Data were collected at baseline and at 12 and 24-weeks following the completion of the intervention. In the group with functional exercise training with verbal stimulation, in comparison to the group with basic exercises, the greatest positive short-term impact of intervention was demonstrated in terms of functional fitness (increased by 1.31 points; 95% confidence interval (CI) = 0.93–1.70), gait speed (improved by 0.17 m/s, 95% CI = 0.13–0.22), hand grip strength (by over 4 kg; 95% CI = 2.51–4.95), and upper-limb flexibility (by 10 cm; 95% CI = 5.82–12.65). There was also a significant increase in the level of free-time physical activity and an improvement in the quality of life, especially as expressed in the domain of overall physical functioning. Our study showed that a functional exercise program, combined with verbal stimulation, is effective at improving physical fitness and raising the level of free-time physical activity.

**Keywords:** sedentary behaviour; aged; exercise; motivation

#### **1. Introduction**

In recent years, there has been a slowdown in the demographic development of people in Europe and Poland. At the end of 2017, the number of people aged 65 and older in Poland amounted to six million, of which over 105,000 were covered by institutional care [1,2]. While changes in care and health policies and services have propagated alternative, long-term care methods, around 25% of older people spent the last years of their lives in a care home [3].

A low level of physical activity (PA) is one of the most serious health problems facing older people [4]. A lack of PA increases the incidence of cardiovascular diseases, reduces cardiovascular and respiratory function, and increases the risk of falling, osteoporotic fractures and disability [5]. According to a report published by the American Journal of Clinical Nutrition, a sedentary lifestyle accounts for twice as many deaths in Europe as obesity. Moreover, increasing PA levels among Europeans would reduce the deaths in Europe by 7.5%, as reported by Ekelund et al. [6]. Encouraging even a slight increase in activity, with reference to inactive people, can be beneficial to public health.

An insufficient level of PA is one of the main behavioural burdens in the world [7]. From 60% to 70% of older people do not meet the World Health Organization's recommendations, with respect to PA, to achieve health benefits [8]. The nationwide Polish data compiled by Kozdro ´n show that only 7% of people aged 60–64 and 0.6% aged 80 years and more undertake regular physical activity [9]. Research conducted in nursing homes indicates that their residents are physically inactive most of the time and do not interact with each other or medical personnel [10].

There are a number of factors in the daily life of older people that can hinder PA. These include, among other things, a negative exercise history, lack of exercise skills, low social and cultural support, and a low level of motivation and self-efficacy [11]. According to Resnick et al. [12], interventions that focus on teaching older people about the benefits of PA, setting goals for exercise program implementation, and reducing unpleasant exercise-related sensations can improve regular participation in exercises and functional performance [13]. Another important element influencing whether an older person is able and willing to participate in physical activity and a model of healthy behaviours is motivation. Motivation is a term that defines the process regulating behaviour that is designed to control the engagement, maintenance, and termination of activities.

Despite the publication of several systematic reviews concerning the effectiveness of exercise programs for older people, the most effective of them has not been clearly identified yet. A systematic review of Carode et al. [14] showed that a multi-component intervention is the best strategy to improve the functional state of older people. Marcos-Pardo et al. developed a motivational resistance-training program and demonstrated the positive effect of training on motivational variables and the body composition of older people. However, the described results concern a preliminary study with a small number of people affected by the intervention [15]. In a systematic review, Farrance et al. indicated that programs for group exercises that used social support proved to be an effective way to improve physical fitness and to increase the level of PA for older people [16]. The authors noted that incorporating education about exercise benefits, social ties, and professional advice on enhancing health behaviours, with reference to exercise programs, could provide guidelines for designing innovative interventions in order to improve the health of older people. The International Association of Gerontology and Geriatrics (IAGG) Global Aging Research Network and the IAGG European Region Clinical Section have developed recommendations regarding motivation and pleasure as key factors to increase the level of PA in people receiving long-term care [17]. Experts have argued for the development and implementation of long-term care improvement strategies to improve the health of residents. Therefore, the aim of the project was to assess the degree of improvement in functional performance and the possibility of changing habitual ways of spending free time among elderly people under institutional care, by applying physical training with verbal stimulation. We hypothesized that the biggest changes regarding the functional efficiency and use of free time will be observed in the group with functional exercise training connected to verbal stimulation.

#### **2. Materials and Methods**

#### *2.1. Trial Design*

Our study contained a controlled, randomized trial with four open-label parallel groups. The study was conducted from March 2016 to December 2018. Data were collected at baseline and at 12 and 24-weeks. This procedure was established according to the "CONSORT" statement [18]. The study was registered in the Sri Lanka Clinical Trials Registry (SLCTR / 2016/004).

Availability of data and materials: All data used in this study were stored at https://repozytorium. ur.edu.pl/handle/item/5094.

Ethics approval and consent to participate: The research project was accepted by the Bioethics Committee of the University of Rzeszow (Resolution No. 6/06/2015). In accordance with the Declaration of Helsinki, the participants were provided with information about the aim and the course of the study, and expressed their written and informed consent to participate. The older persons were informed about the possibility of withdrawing from the study at any point during the study procedures.

#### *2.2. Participants*

The study was conducted in nine randomly selected nursing homes for older people and the chronically physically ill in Southeastern Poland. The management department of the centers were informed about the objectives and conduct of the study. After obtaining permission to implement the project in individual centers, the recruitment of participants began. To promote the exercise programs, information was posted, leaflets were distributed, and residents were orally informed about the details. The initial qualification for participants in the study was made by a physiotherapist working in the center. Participants who were eligible for the trial were required to comply with the following criteria: age 65–85 years, Mini-Mental State Examination (MMSE) score >19, Geriatric Depression Scale (GDS) score <11 points, physical fitness without serious restrictions, Short Physical Performance Battery score >5, and spending free time sitting for at least 4 h/day, 6 to 7 days/week (the Physical Activity Scale for the Elderly questionnaire). Exclusion criteria were: symptoms of cardiovascular diseases, severe systemic disease, severe circulatory or organic insufficiency, severe neurological disorder, injuries of the lower limbs during the last 6 months, use of medication significantly affecting the body's balance and participation in improvement exercise programs in the 3 months prior to the trial. Subsequently, an interview was conducted with a physician employed in the nursing home to eliminate the health contraindications in performing physical exercise by selected residents. After taking into account the inclusion criteria and obtaining written consent from the physician and residents to participate in the study, 204 people were included in the exercise program

#### *2.3. Interventions*

The subjects were assigned, at random, to one of four groups: Group BE: Basic exercises without verbal stimulation Group BE + VS: Basic exercises combined with verbal stimulation Group FET: Functional exercise training without verbal stimulation Group FET + VS: Functional exercise training with verbal stimulation

#### Exercise Program

All study participants took part in a 12-week exercise program, with or without verbal stimulation. Exercises were conducted in groups of 4–8 people, twice a week for 30 min. Each session was adapted to the functional capabilities of the subjects and was supplemented with breathing exercises. The exercise intensity was moderate, at 11–13 points, according to the Borg scale. The load during resistance training was up to 60% of one repetition maximum. Participants exercised with the music preferred by the subgroup (low volume level of 60 dB, moderate tempo). Exercise programs were performed by 9 physiotherapists (one physiotherapist per care home) with at least 2 years of experience working with older people. Each therapist was trained in the field of exercise programs and verbal stimulation before starting the program. They also dealt with the assessment of participants in the exercise programs, and monitored possible pain or other complications resulting from the performed exercises. Their observations were noted in activity diaries prepared for each group. In the case of health problems, such as malaise—a pain caused by excessive effort—the physician supervising the research made the decision to exclude participants from the study. Furthermore, the blood pressure and pulse of the older people were monitored before and after exercise. In addition, the study director was in contact with

all physiotherapists in the course of the intervention in order to ensure that the exercise was of high quality and consistent in all care homes.

Basic exercises: the program included exercises performed in a sitting position. The exercises contained elements of aerobic fitness, stretching and equivalent exercises.

Functional exercise training: the program was divided into two sessions. Session I contained strengthening and stretching, with exercises performed in a sitting position using a Thera-Band and gymnastic sticks. Lower-limb strengthening exercises included tasks such as dorsi flexion and plantar flexion of the ankle joints, flexion and extension of the knee joints, flexion, extension and abduction in the hip joints, standing up and sitting down on a chair, and lifting objects from the floor. Upper-body exercises included stretching and strengthening of the shoulder girdle. Session II contained equivalent and functional training, using exercises performed in a seated or standing position, using chairs as stabilizing aids. Functional exercises included complex motor tasks, such as head rotation when sitting and standing, changing the body position, and lifting objects from the floor and keeping them. Balance exercises included exercises performed with and without visual control; static and dynamic balance of the elderly people was practiced (physical support was provided by a physiotherapist and auxiliary aids). The progression of the balance exercises was achieved by reducing the support plane, or by eliminating the visual control. Exercises were oriented towards achieving the goals of functional activity established by the elderly people.

Verbal stimulation: a model physical exercise program that incorporates the use of verbal stimulation. The model is focused on studying the achievements of participant's in regard to (objective) functional goals, and altering his/her (subjective) perception of the intensity of the training program and their individual aims. Before starting the intervention, a systematic review was performed to assess which elements had the greatest impact on health benefits among older people. The next step was to determine the baseline assessment; therefore, both the short- and long-term objectives of exercise participation were established. Short-term objectives assessed what a person is able to perform while exercising daily (e.g., perform 20 sit-ups, which improves lower extremity strength), whereas long-term objectives determined the "ultimate goal" (e.g., walking to the shop unaided or generally obtaining an improved level of mobility). Furthermore, specified objectives were helpful in achieving individual goals, as well as in persevering with these new health behaviours. According to the results of the studies carried out by Park et al., setting functional goals is an important motivating factor for PA performed by older people [19].

The program uses:


In addition, informative materials were provided to the subjects:


According to Locke, education and discussion about the anxiety connected to physical activity allows an older person to feel the need to participate in exercises [21].

The verbal stimulation program was included in the individual exercise programs.

#### *2.4. Outcome Measures*

Outcome assessments were performed at the baseline and at 12 and 24-weeks. The study was divided into two stages. On the first day, sociodemographic data and questionnaire interviews were collected; on the second day, anthropometric measurements and functional activity tests were performed.

Data regarding age, sex, education, marital status, and years in a nursing home were gathered on the basis of the records kept by care homes and by interviews with the individuals researched. Data related to chronic diseases and the number of drugs were collected from medical records kept by physicians in care homes. Cognitive status was also assessed by MMSE [22] and depression symptoms were assessed by the use of GDS [23].

#### 2.4.1. Main Outcome

The Short Physical Performance Battery (SPPB) test was used to assess the functional status of the participants. The test comprised the assessment of three physical sequences: maintaining balance in three positions, gait speed over a short distance and attempting to stand up from a chair five times without the use of the upper limbs [24].

#### 2.4.2. Secondary Outcomes

#### Physical Activity Assessment

Physical activity was assessed by means of the Physical Activity Scale for the Elderly (PASE) [25]. It is based on the evaluation of how free time was spent, as well as the work-related activities or voluntary work performed within 7 days of the survey, taking into account the frequency, duration and the level of intensity of these activities.

#### Functional Assessment

The performance of basic and complex everyday activities was assessed using the activities of daily living and instrumental activities of daily living (ADL-IADL) scale [26].

#### Muscular Strength Assessments

Hand grip strength (HGS) was carried out by the use of a hand dynamometer (JAMAR PLUS + Digital Hand Dynamometer, Patterson Medical). The values were obtained from measurements carried out on the participants while seated on a chair without armrests, with their feet rested flat on the floor—In pursuance to the recommendations of the American Society of Hand Therapists [27]. The average of the three measurements was recorded. The 5× Sit to Stand Test (5× STS) was used to assess the strength of the lower limbs. The participants were required to stand up 5 times from a sitting position as fast as possible without using their upper extremities [28].

#### Mobility Assessment

Mobility was assessed using the Timed Up and Go test (TUG) without a cognitive task and with a cognitive task (TUG cog) [29]. The TUG test was performed as follows: the participant will stand (from a sitting position on a chair), walk a distance of 3 m, turn around (180◦ ), walk the 3 m back to the starting position, and resume the sitting position. The final result was the average time of the three attempts. Gait speed was assessed using the 10-Meter Walk Test [30]. Participants were asked to walk a distance, marked with an adhesive tape, of 10 m.

#### Flexibility Assessment

The elasticity of the upper and lower limbs was assessed using the back stretch test (BS) and the chair sit and reach test (CSR) [31]. BS estimates the elasticity of the girdle of the upper limb, which is necessary in the course of performing such activities as rubbing and washing the back. The test consisted of griping the hand of one limb from above with the other hand from below and behind the subject's back. The distance between the fingertips of the middle fingers was measured. CSR assessed the elasticity of the lower body, which was necessary in order to maintain the correct pattern of walking, getting out of the bathtub or dressing socks. The test was to bend the body in a seated position towards the outstretched lower limb. The distance between fingertips and toes was measured.

#### Body Balance Assessment

Balance was assessed using the Berg balance scale (BBS) [32]. The scale included 14 simple tasks, including: changing body position, maintaining a sitting position, maintaining a standing position under visual control and without it, watching, standing in a tandem position, standing on one leg, rotation around the axis, reaching forward, lifting objects from the floor, transferring, and going up a step.

#### *2.5. Other Outcomes*

#### 2.5.1. Postural Stability Assessment

The assessment of the postural stability was performed by the use of a two-plate stability platform CQ Stab 2P (CQ Elektronik System, Czernica, Poland). Each of the platform plates had 3 force sensors that determined the displacement of the center of pressure on the support plane. During the measurements, the values describing the static balance were recorded. Platform plates were placed parallel, 2 m from the wall of the room where there was a marker to fix eyesight during the test with open eyes. Before each set of measurements was taken, the device was calibrated. The test included a 30 s sample performed with eyes open and eyes closed. The participants were instructed to remove their shoes and take a free-standing position on the platform plates with their arms set adjacent to the torso [33].

All testing procedures were fully explained and presented prior to assessment.

#### 2.5.2. Quality of Life Assessment

Quality of life (QoL) was examined using the SF-36v2 questionnaire, consisting of 36 questions, which analysed the functional profile of health, well-being and psychometric assessment based on the subject's mental state of health. The quality of life established with respect to physical health was measured using two main domains: functioning in the physical dimension, i.e., general physical health (physical component summary: PCS), and functioning in the mental dimension, i.e., general mental health (mental component summary: MCS) [34].

#### *2.6. Sample Size*

The sample size was estimated from an a priori power analysis to detect the statistically significant effects of exercise [35]. The sample size was chosen according to the Cohen method, using standard assumptions: 0.05 for significance level, 0.8 for power of test, and 0.5 for effect size, accounting for, according to Cohen, a medium effect size [36]. The sample size calculation for the main outcome measure was based on changes in SPPB scores. The sample size calculation was based on 80% power to detect a one-point change in the SPPB score with an alpha level of 0.05. It was calculated that, based on the final analysis, the total number of people surveyed should amount to 39 people in each group. Therefore, 51 people were recruited to individual groups in order to allow for a 20% dropout rate from the study.

#### *2.7. Randomization and Blinding*

Randomization that implemented the stratified method by the use of the statistical package R 3.2.2 (The R Foundation for Statistical Computing, Vienna, Austria) was carried out. Four-in-one blocks were randomized, which made it possible to obtain an even distribution of elderly people in the studied groups. The order of randomization was determined by using a computerized schedule of random numbers. An independent biostatistician implemented randomization, hid the block size from the executive module and used randomly mixed block sizes. He was responsible for the confidentiality of the list of people included in the study. Outcome assessors were blind to the group division and did not take part in implementing interventions. Due to the ensemble nature of care homes, participants in the study were not blinded after being assigned to groups.

#### *2.8. Statistical Methods*

Descriptive characteristics were presented as a mean and standard deviations, or a number and percent when appropriate. A one-way ANOVA test was used to assess the differences between groups. The mean difference between treatment groups and the confidence intervals for quantitative variables was also determined. Post-hoc analysis for the quantitative variables analysis was conducted with *t*-tests with Bonferroni correction. The significance of changes in the examined variables, between two time points, were assessed with paired *t*-tests. Standard intention-to-treat analysis was performed for each outcome. Missing data were deemed to be missing at random and were calculated using the imputation technique according to the protocol study [37]. Analyses were conducted at a 0.05 level of significance. R software version 3.6.1 (The R Foundation for Statistical Computing, Vienna, Austria) was used.

#### **3. Results**

After the initial test was performed and the inclusion and exclusion criteria were taken into account, the older people were randomly assigned to four exercising groups: BE group, 51 people; BE + VS group, 51 people; FET group, 51 people; and FET + VS group, 51 people (Figure 1). The withdrawal rate from the study was: BE group, 10 people; BE + VS, 12 people; and FET, 10 people and FET + VS, 9 people. The main reasons for withdrawal from the study were: moving house, influenza diagnosed by a physician, refusal to participate without any reason given, and the death of a participant. The analysis included people whose attendance at exercises was over 80%.

In the studied groups, baseline parameters did not differ across the groups in terms of sociodemographic features and clinical parameters, including: cognitive status, mood, functional state, mobility, muscle strength, flexibility, body balance, postural stability with and without visual control, quality of life and level of physical activity. The average age of the study groups fluctuated between 73 and 74 years. Baseline scores of the research variables are presented in Table 1. Postural balance characteristics of the participants can be found in Supplementary Materials, Table S1.

**Figure 1.** Flow diagram of the intervention study. ITT, intention-to-treat.




SD, Standard Deviation; BMI, body mass index; GDS, Geriatric Depression Scale; MMSE, Mini-Mental State Examination; SPPB, Short Physical Performance Battery; PASE, Physical Activity for Elderly; ADL, Activity of Daily Living; IADL, Instrumental Activity of Daily Living; HGS, Handgrip Strength; 5× STS, 5× Sit to Stand; TUG, Timed Up and Go; TUG cog, Timed Up and Go cognitive; BS, Back Stretch; CSR, Chair Sit and Reach; BBS, Berg Balance Scale.

Regarding the BE group, after 12 weeks of exercises, a statistically significant improvement was noticed in the following areas: functional fitness, muscle strength of lower limbs, mobility and gait speed, and flexibility of the lower limbs. The observed improvement was only maintained for the following 12 weeks in terms of lower-limb flexibility.

In the BE + VS group, after 12 weeks of exercises, a statistically significant improvement was shown in regard to functional fitness, performing complex everyday activities, hand grip and lower-limb strength, flexibility of the upper and lower limbs, body balance, as well as the quality of life of the people studied. The obtained change was maintained in most of the aforementioned parameters until 24 weeks after the exercises began.

The largest positive changes were observed in the groups with FET and FET + VS. In the group FET + VS, the greatest positive short-term impact of intervention was demonstrated in terms of functional fitness (SPPB increased by 1.31 points; 95% CI = 0.93–1.70), gait speed improved by 0.17 m/s (95% CI = 0.13–0.22), hand grip strength enhanced over 3.5 kg (95% CI = 2.51–4.95) and flexibility of

the upper limbs developed by 10 cm (95% CI = 5.82–12.65). There was also a significant increase in the level of physical activity spent in free time (an increase by 6.91 PASE score; 95% CI = 4.58–9.24) and an improvement in the quality of life, especially in the domain of overall physical functioning (an increase by 11.79 score; 95% CI = 8.64–14.95).

The groups exercising with a verbal stimulation element were characterized by maintaining improvement in most of the studied parameters for a period of 24 weeks from the beginning of the study (Table 2). A mean difference scores for each group across time in terms of postural balance can be found in Supplementary Materials, Table S2.

In order to assess the differences between the four groups (BE, BE + VS, FET, and FET + VS), a one-way ANOVA analysis was applied. After 12 weeks of exercises, there was a statistically significant difference between the BE and FET + VS groups. In the FET + VS group, functional fitness, mobility without a cognitive task, flexibility of the upper and lower limbs, hand grip and lower-limb strength, balance and quality of life in the physical domain significantly improved, in comparison to the BE group (SPPB 0.25 vs. 1.27; TUG −0.91 vs. −3.89; HGS <sup>R</sup> −0.65 vs. 3.63; 5× STS −2.55 vs. −6.36; BS <sup>R</sup> 1.57 vs. 9.27; and BBS 1.18 vs. 7.27). All the studied groups after the intervention improved, in a similar way, their ability to perform basic and complex everyday activities, mobility with a cognitive task, and quality of life in the mental domain (Table 3). No statistically significant difference between groups was observed in body balance parameters after 12 weeks of exercise (Supplementary Materials, Table S3).

After 24 weeks of commencing exercises, the greatest effects were noted in the FET + VS group, in comparison to the BE group in most of the studied parameters besides lower-limb flexibility and quality of life in the mental domain. A significantly stronger short-term impact of interventions in the FET + VS group was demonstrated in the range of improvement of functional fitness and changes in the habit of spending free time among older people (*p* < 0.001). In the FET + VS group, compared to the other exercising groups (BE, BE + VS, FET), there were statistically significant, larger positive changes in the functional fitness, leisure-time activity, performance of complex daily activities, mobility, gait speed, and quality of life in the physical domain (*p* < 0.001) (Table 4). No statistically significant difference between groups was observed in body balance parameters after 24 weeks follow-up (Supplementary Materials, Table S4).


**2.**Meandifferencescoresforeachgroupacross

 *9*, 477



**Table 2.**Mean difference scores for each group across time.

\* statistically significant result. SPPB, Short Physical Performance Battery; PASE, Physical Activity for Elderly; ADL, Activity of Daily Living; IADL, Instrumental Activity of Daily Living; HGS, Handgrip Strength; 5×STS, 5×Sit to Stand; TUG, Timed Up and Go; TUG cog, Timed Up and Go cognitive; BS, Back Stretch; CSR, Chair Sit and Reach; BBS, Berg Balance Scale.



**Table 3.**Between-group comparisons at 12 weeks.

 \* statistically significant result. SPPB, Short Physical Performance Battery; ADL, Activity of Daily Living; IADL, Instrumental Activity of Daily Living; HGS, Handgrip Strength; 5× STS,5× Sit to \* statistically significant result. SPPB, Short Physical Performance Battery; ADL, Activity of Daily Living; IADL, Instrumental Activity of Daily Living; HGS, Handgrip Strength;5×STS, 5×Sit to Stand; TUG, Timed Up and Go; TUG cog, Timed Up and Go cognitive; BS, Back Stretch; CSR, Chair Sit and Reach; BBS, Berg Balance Scale.



**Table 4.** Between-group comparisons at 24 weeks.

\* statistically significant result. SPPB, Short Physical Performance Battery; PASE, Physical Activity for Elderly; ADL, Activity of Daily Living; IADL, Instrumental Activity of Daily Living; HGS,HandgripStrength;5×STS,5×SittoStand;TUG,TimedUpandGo;TUGcog,TimedUpandGocognitive;BS,BackStretch;CSR,ChairSitandReach;BBS,BergBalanceScale.

#### **4. Discussion**

Observational studies suggest that 97% of daytime is spent sedentarily by residents of nursing homes, e.g., sitting and watching TV with low levels of interaction with each other and with medical staff [38]. A lack of engagement with PA has a detrimental effect on physical and mental health, quality of life and social isolation [39]. Therefore, reducing sedentary behaviour is an important new modifiable variable of lifestyle that can improve the health of older people [40]. According to the Copenhagen Consensus statement (2019) that considers PA and aging, researchers determined that self-efficacy, intentions, and the perceptions of one's health are related to the person's level of PA and interventions based on the theory that behavioural changes provides greater results. According to this account, they concluded that future research should assess the potential of these factors to promote PA and the good health of seniors [41].

To the best of our knowledge, this is the first intervention that assesses the impact of exercise programs, combined with verbal stimulation, aimed at motivating people to improve physical fitness and at changing habitual ways of spending free time by older people in institutional care. Furthermore, we have observed that the functional exercise program, combined with verbal stimulation, is the most effective in improving functional fitness, mobility, muscle strength and flexibility, as well as increasing the level of physical activity spent in free time and improving quality of life, especially within the physical domain.

Motivational strategies included in a resistance-training program affected psychological needs, motivation and compliance with the physical-activity principles [15]. Findings on interventions that increased the level of PA in free time are of moderate quality and focus mainly on systematic reviews, indicating a number of guidelines for the techniques used in order to change adult behaviour [42,43]. A systematic review by Orrow et al. [44] showed that the promotion of PA used in older people with a "sedentary" lifestyle leads to a small or medium improvement in the level of physical activity over 12 months. Hilldson et al. demonstrated, in their systematic review, that physical exercise programs moderately affect the functional state of older people and cause changes in the level of PA [45]. They suggested that further research should be planned with a view to propagate the long-term involvement in physical exercises by older people. Taking into account the results of the research herein, and the reports of other authors, when further designing an intervention in order to change the habit of older people in free time and to improve the health and quality of life of older people, it is necessary to focus not only on performing physical exercises at a moderate intensity, but also on the use of verbal stimulation based on generating motivation to replace the time spent sitting down with physical activity.

In our study, the effectiveness of four different exercise programs were compared. Despite the publication of several systematic reviews on the effectiveness of exercise programs for older people, as of yet, the most effective has not been clearly identified [14,46,47]. According to the review carried out by Silva et al., although exercise-based interventions have a positive impact on the physical functioning and wellbeing of older people, the most effective exercise program in this population remains unidentified [48]. Crocker also indicates that the physical rehabilitation of residents in nursing homes can be effective; however, there is no evidence regarding improvements in sustainability, cost-effectiveness, or which interventions are the most appropriate [49]. Regarding our study, we have shown that, after 12 weeks of exercise training, both the group with basic exercises and functional exercises, with or without verbal stimulation, have a positive effect on improving the physical fitness and quality of life of older people. Other authors have also confirmed that, regardless of the exercise program used, 12 weeks of physical training has a beneficial effect on the functional state of older people [50]. However, de Vreede et al. indicated that the beneficial effect of exercise is lost after suspending activity [51].

Taking everything into consideration, the implemented functional exercise program with verbal stimulation turned out to be the most effective with respect to the short-term effects of the intervention. The greatest positive changes were noted in the performance of complex daily activities, functional

fitness of the lower limbs, gait speed and quality of life in the physical domain. In the FET + VS group, after 24 weeks, 1.31 points of improvement were obtained in the SPPB test; 4.13 s improvement in the TUG test; and 7.31 points in the BBS test. These values are higher than the suggested minimum clinically important difference for these tests [52,53].

Providing residents of nursing homes with group physical interventions is profitable and safe. It affects the reduction of disability—recording rare adverse events [54]. As for the residents of nursing homes, maintaining an adequate level of physical and psychological functions, enabling them to perform basic and complex everyday activities, allows them to have control over their own lives. Complete dependence on the help of others is the cause of emotional suffering and feelings of helplessness. According to Prat and Scheicher [55], the loss of functional independence is one of the main problems of older people, while independence increases their satisfaction and improves their quality of life. Weeks et al. [56] stated that preventing the expansion of functional limitations is a key factor motivating older people to participate in physical exercise. An additional element affecting the functioning of older people in nursing homes is the ensemble nature of the institution. In order to improve interactions with other residents, collective training should be used to strengthen social relationships and help to maintain interpersonal harmony, which is necessary for a peaceful life in the facility.

Our study has some limitations. First, there was no research examination performed 36 weeks after the start of the intervention due to the high drop-out rate caused by the increased incidence of influenza among older residents in the nursing homes. Secondly, the collective nature of the facilities means that it was not possible to implement double-blinding. In the case of further studies, additional measurement points should be added after six and 12 months from the beginning of the intervention.

#### **5. Conclusions**

In summary, the short-term evaluation showed that a functional exercise program, combined with verbal stimulation, is effective in improving physical fitness and raising the level of physical activity spent in free time. To accomplish a sustained functional efficiency and PA change, a prolonged follow-up is required. Finally, the group exercise program is safe and can be implemented into routine practice. Therefore, nursing home staff, as well as relatives, should be involved in the development and implementation of changes aimed at reducing the time spent passively by older people in institutional care.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2077-0383/9/2/477/s1, Table S1: Postural balance characteristics of the participants, Table S2: Mean difference scores for each group across time, Table S3: Between-group comparisons in postural balance at 12 weeks, Table S4: Between-group comparisons in postural balance at 24 weeks.

**Author Contributions:** Conceptualization, A.W.-S.; Data curation, A.W.-S.; Formal analysis, A.W.-S. and B.S.; Investigation, A.W.-S. and N.W.; Methodology, A.W.-S. and A.C.-S.; Project administration, A.W.-S.; Supervision, ´ A.W.-P.; Writing—original draft, A.W.-S.; Writing—review & editing, A.W.-S.; A.C.-S.; N.W.; B.S.; and A.W.-P. All ´ authors have read and agreed to the published version of the manuscript.

**Funding:** This study was supported by the funds for statutory research of the University of Rzeszow.

**Acknowledgments:** The authors would like to thank the study participants for their collaboration.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

*Article*

### **E**ff**ects of a Multicomponent Exercise Program in Physical Function and Muscle Mass in Sarcopenic**/**Pre-Sarcopenic Adults**

**Hyuma Makizako 1,\*, Yuki Nakai <sup>1</sup> , Kazutoshi Tomioka 2,3, Yoshiaki Taniguchi 2,4 , Nana Sato 2,3, Ayumi Wada 2,3, Ryoji Kiyama <sup>1</sup> , Kota Tsutsumimoto <sup>5</sup> , Mitsuru Ohishi <sup>6</sup> , Yuto Kiuchi <sup>2</sup> , Takuro Kubozono <sup>6</sup> and Toshihiro Takenaka <sup>3</sup>**


Received: 22 April 2020; Accepted: 6 May 2020; Published: 8 May 2020

**Abstract:** This study aimed to assess the effects of a multicomponent exercise program on physical function and muscle mass in older adults with sarcopenia or pre-sarcopenia. Moreover, we aim to standardize the exercise program for easy incorporation in the daily life of community-dwelling older adults as a secondary outcome. A single-blind randomized controlled trial was conducted with individuals (≥60 years) who had sarcopenia or pre-sarcopenia (*n* = 72). Participants were randomly assigned to the exercise and control groups. The exercise program consisted of 12 weekly 60-min sessions that included resistance, balance, flexibility, and aerobic training. Outcome measures were physical function and muscle mass. Assessments were conducted before and immediately after the intervention. Among the 72 participants (mean age: 75.0 ± 6.9 years; 70.8% women), 67 (93.1%) completed the trial. Group-by-time interactions on the chair stand (*p* = 0.02) and timed "up and go" (*p* = 0.01) tests increased significantly in the exercise group. Although the exercise group showed a tendency to prevent loss of muscle mass, no significant interaction effects were observed for cross-sectional muscle area and muscle volume. The 12-week exercise program improved physical function in the intervention group. Although it is unclear whether the program is effective in increasing muscle mass, a multicomponent exercise program would be an effective treatment for physical function among older adults with sarcopenia.

**Keywords:** muscle strength; sarcopenia; resistance training; randomized controlled trial

#### **1. Introduction**

Sarcopenia is defined as a general loss of skeletal muscle mass and strength and is considered a major health problem for older individuals [1,2]. In 2016, sarcopenia was recognized as an independent condition by the International Classification of Disease, Tenth Revision, Clinical Modification (ICD-10-CM), code (i.e., M 62.84) [3].

Over the last decade, several clinical diagnostic criteria for sarcopenia have been reported worldwide [4–9]. In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) published its recommendations for a clinical definition and consensual diagnosis criteria [4]. Subsequently, many cohort studies identified sarcopenia based on these criteria, which include a combination of muscle mass and strength, and physical function loss [10,11]. In Asia, the most widely utilized criteria for determining sarcopenia are based on the Asia Working Group for Sarcopenia (AWGS) consensus, published in 2014 [8].

According to a previous systematic review that utilized the EWGSOP definition, the prevalence of sarcopenia is 1%–29% in community-dwelling populations and 14%–33% in long-term care populations with regional and age-related variations [12]. In the Asian population (Taiwan), the prevalence of sarcopenia varied from 3.9%–7.3% [13]. According to the AWGS criteria, the prevalence is estimated to range between 4.1% and 11.5% in the general older population [14]. A previous review and meta-analysis showed that the pooled prevalence of sarcopenia based on AWGS criteria among Japanese community-dwelling older individuals is 9.9%; similar prevalence rates were found in older men (9.8%) and women (10.1%) [15]. The numbers of people who had sarcopenia increased to 11%–50% for those aged 80 or above [16]. Community-dwelling older adults with sarcopenia have the worse physical performance [13,17] and are associated with premature mortality [18]. Since almost 10% or more of older individuals may meet the criteria for sarcopenia, effective prevention and improvement strategies are necessary.

Much interest has focused on community-based interventions for treating sarcopenia. A current systematic review and meta-analysis showed positive effects of exercise and nutritional interventions for older individuals [19]. However, there is little evidence of these effects, and the literature concludes that the evidence quality ranges from very low to low [19]. Therefore, well-designed randomized controlled trials (RCTs) to assess the effects of exercise on physical function and body composition, especially muscle mass, should be promoted.

Few well-designed intervention studies with a sufficient sample size have been conducted on the effects of exercise programs on sarcopenia. There is no effective treatment for sarcopenia, but physical exercise seems to be highly effective at counteracting the decline in physical function, muscle mass, and strength associated with ageing. The primary outcome of the present RCT was to investigate the effects of a multicomponent exercise program on physical performance and muscle mass in community-dwelling older adults with sarcopenia or pre-sarcopenia. Furthermore, as a secondary outcome, we aimed to standardize this approach for community-dwelling older adults, which can be easily incorporated into their daily lives.

#### **2. Methods**

#### *2.1. Study Design*

This community-based intervention study was a single-blind randomized controlled trial (UMIN 000036614). The intervention programs were implemented between June and September 2019. All participants provided written informed consent; after baseline measurements, they were randomly allocated to a 12-week multicomponent exercise program group or a wait-list control group. The study was approved by the Ethics Committee of the Faculty of Medicine, Kagoshima University (#180273).

#### *2.2. Participants and Selection Criteria*

We assessed 1151 community-dwelling adults aged 40 years or older who were enrolled in the Tarumizu study in 2018. Each participant was recruited from Tarumizu, a provincial city in Kagoshima Prefecture, Japan, between July and December 2018. Figure 1 presents the study flow. A total of 332 potential participants (≥60 years) with muscle mass loss (e.g., sarcopenia or pre-sarcopenia) were identified. Skeletal muscle mass loss was assessed by multi-frequency bioelectrical impedance analysis using the InBody 470 (InBody Japan, Tokyo, Japan). Appendicular skeletal muscle mass (ASM) was derived as the sum of the muscle mass of the four limbs, and the ASM index (ASMI, kg/m<sup>2</sup> ) was calculated. Skeletal muscle mass loss was determined based on the AWGS criteria for sarcopenia: ASMI < 7.0 kg/m<sup>2</sup> for men and <5.7 kg/m<sup>2</sup> for women [8]. Participants with skeletal muscle mass loss and low physical function (low grip strength < 26 kg for men or <18 kg for women, and slowness, indicated by normal walking speed < 0.8 m/sec), were determined to have sarcopenia, and those with skeletal muscle mass loss without low physical function were determined as having pre-sarcopenia [20]. Individuals who did not use Japanese long-term care insurance and had a history of hip or knee operations, femoral neck fracture, stroke, Parkinson's disease, Alzheimer's disease, or other severe brain diseases, were excluded from the sample (Figure 1).

**Figure 1.** Flow diagram indicating participant progress through the trial.

#### *2.3. Intervention*

Following randomization, individuals in the exercise training group participated in a progressive multicomponent exercise program over 12 weeks of supervised 60-min sessions that commenced in June 2019. The intervention consisted of resistance training, balance, flexibility, and aerobic exercises.

Thirty-six participants in the exercise groups were divided into two classes conducted by physiotherapists and instructors at a community center. Before each session, the participants checked their vital signs, including blood pressure, pulse rate, and self-reported physical condition. If vital signs were unsuitable, such as systolic blood pressure ≥ 180 mmHg, diastolic blood pressure ≥ 110 mm Hg, or resting pulse rate ≥ 110 bpm or ≤ 50 bpm, participants were asked to avoid exercise that day. Each session began with a brief warm-up involving stretching, followed by 25 to 30 min of resistance training, 20 to 25 min of balance and aerobic exercises, and 5 min of cool-down. Resistance training used a progressive sequence based on individual strength performance, starting with no resistance load (own weight) for the first two weeks. Progressive resistance was provided by resistance bands (TRIPLE TREE, Carbro Flavor USA Inc., CA, USA) that had five resistance levels. Individuals' strength performance was tested every two weeks to determine the resistance load (intensity of resistance bands) and accordingly increase it for the next two weeks. In the strength performance test, participants determined their suitable resistance load at 12 to 14 on the Borg rate of perceived exertion scale [21], through ten repetitions of knee extensions. For each resistance exercise, participants completed up to ten repetitions of each movement, which included: (1) knee extension (quadriceps), (2) hip flexion (knee raises) (psoas major and iliacus), (3) hip internal rotation (gluteus medius and minimus), (4) elbow flexion and shoulder abduction (trapezius and rhomboid), (5) elbow flexion and trunk rotation (pectoralis major and oblique abdominis), (6) hip extension (gluteus maximus), (7) knee flexion (hamstrings), (8) hip abduction (gluteus medius), and (9) squat (quadriceps, gluteus maximus, and hamstrings). Balance training included a tandem stand, heel-up stand, one-leg stand, weight shifts, and stepping (anterior-posterior and lateral), to improve static and dynamic balance ability. Aerobic exercise consisted of anterior-posterior or lateral stepping repetitions for six minutes. The participants also performed daily home-based exercises, which were self-monitored using booklets, and were encouraged to record an exercise calendar. Exercise class attendance rate was calculated through the 12 exercise sessions as an exercise program adherence.

Participants in the wait-list control group (henceforth referred to as the control group) were asked to maintain their daily activities and attend a 60-min education class once during the trial period. The topic of this class was an irrelevant theme (e.g., preventing billing fraud).

#### *2.4. Outcome Measures*

#### 2.4.1. Physical Function

Grip strength and gait speed, performance on the chair stand test and timed "up & go" (TUG) were assessed to determine physical function and sarcopenia status, as recommended by EWGSOP2 and AWGS2 [22,23]. All assessments were administered by well-trained, licensed physical therapists.

Grip strength was measured in kilograms for the participant's dominant hand, using a Smedley-type handheld dynamometer (GRIP-D; Takei Ltd., Niigata, Japan) [24].

Gait speed was measured in seconds using infrared timing gates (YW; Yagami Ltd., Nagoya, Japan). Participants were asked to walk on a flat, straight, 10 m-long walk path, at both usual and maximum gait speeds. Infrared timing gates were positioned at the 2 m mark and at the end of the path.

The chair stand test involved standing up from a sitting position and sitting down five times as quickly as possible without pushing off [25]. Physical therapists recorded the time a participant took to perform this action with their arms folded across their chests. The fifth repetition was recorded in seconds using a stopwatch (timed to 0.1 s).

In the TUG test, the participant rose from a standard chair, walked a distance of 3 m at a normal and safe pace, turned around, walked back, and sat down again [26]. Time was measured once in seconds, using a stopwatch.

#### 2.4.2. Cross-Sectional Muscle Area/Muscle Volume

Cross-sectional muscle area and muscle volume measurements were performed using magnetic resonance imaging (MRI), which was performed using a 1.5T MRI MAGNETOM Essenza (Siemens Healthcare, Germany). Imaging of both thighs was performed before and after the intervention period in a supine position with both legs extended. A total of 120 consecutive T1-weighted axial slices with 1.5 mm slice thickness were acquired from the upper edge of the patella. Three levels of cross-sectional muscle area (m<sup>2</sup> ), lower, middle, and upper, were calculated from the right thigh. The lower level was calculated using 30 slices from the upper edge of the patella (45 mm proximal along the thigh). The middle and upper levels were determined using 60 (90 mm proximal along the thigh) and 90 slices (135 mm proximal along the thigh) from the upper edge of the patella, respectively. Muscle volume of the right thigh (cm<sup>3</sup> ) was calculated using 60 consecutive slices between the lower and upper level slices (Figure 2). Image-J (NIH, USA, version 1.3) software was used to analyze the MRI images.

**Figure 2.** Cross-sectional muscle area of the thigh for segmentation and a sample segmented image.

### *2.5. Statistical Analysis*

\* The sample size was calculated using G⋆Power software (version 3.1.9.2) based on a previous study [27], which demonstrated that at least 28 participants were needed for each group to detect a 15% increase in physical functioning. We included 20% more patients in each group because of dropouts observed in our previous studies. The alpha error was defined as 0.05, with a power of 80%. Data have been presented as mean ± standard deviation (SD). All outcome data including physical function and muscle mass were assessed as normally distribution using the Kolmogorov–Smirnov test. Analysis of the intervention effects on outcomes was conducted according to the intention-to-treat principle, with the expectation-maximization algorithm estimation to substitute missing data. Outcome changes were verified by the Student's *t*-test for paired data in each group. The repeated-measures analysis of variance (ANOVA), with group-by-time interaction, was used to evaluate the intervention effects. Data entry and analysis were performed using IBM SPSS Statistics for Windows (version 25.0). A *p*-value of <0.05 was considered statistically significant.

#### **3. Results**

#### *3.1. Participant Characteristics at Baseline*

Figure 1 summarizes the study flow. We screened 72 participants who were eligible and randomized. Participant characteristics and comparisons of baseline assessments between participants in the exercise and the control groups have been presented in Table 1. There were no significant differences in any of the characteristics and outcome measures between the exercise and control groups.


**Table 1.** Participant characteristics at baseline.

Data presented as mean ± SD or number (%). There were no significant between-group differences in baseline characteristics. BMI = body mass index; SPPB = short physical performance battery; ASMI = appendicular skeletal muscle mass index. <sup>a</sup> Missing, *n* =1. <sup>b</sup> Missing, *n* = 7. <sup>c</sup> Lower, a 30-slice section from the upper edge of the patella; middle, a 60-slice section from the upper edge of the patella; upper, a 90-slice section from the upper edge of the patella (1 slice = 1.5 mm thickness).

#### *3.2. Exercise Program Adherence and Adverse Events*

Among the 72 randomized participants, 67 (93.1%) completed the trial. The mean participation rate was 81% for the 12 exercise sessions. No adverse events related to the intervention were reported.

#### *3.3. Sarcopenia-Related Physical Function*

Table 2 and Figure 3 show the pre- and post-intervention changes in sarcopenia-related physical function in the control and exercise groups. The Student's *t*-test for paired data in each group showed that grip strength declined significantly post intervention in the control group (*p* = 0.01), but no change was found in the exercise group. There were no significant changes in normal and maximum gait speeds in the control group, while maximum gait speed showed significant improvement in the exercise group post-intervention (*p* < 0.01). The chair stand performance improved in both groups. The exercise group showed significantly better performance on the TUG test post intervention (*p* < 0.01); no changes were seen in the control group. In the repeated-measures ANOVA, significant group-by-time interactions were observed on the chair stand (F = 5.85, *p* = 0.02) and TUG (F = 6.33, *p* = 0.01) tests, with increases

in the exercise group. There were no significant group-by-time interactions in the other physical function assessments.


**Table 2.** Changes in sarcopenia-related physical function during the 12-week intervention period.

−

Data presented as mean <sup>±</sup> SD. <sup>a</sup> Missing, *<sup>n</sup>* <sup>=</sup> 1 (control group, *<sup>n</sup>* <sup>=</sup> 35).

**Figure 3.** Improvement percentage of sarcopenia-related physical function and muscle mass after intervention.

#### *3.4. Cross-Sectional Muscle Area*/*Muscle Volume*

Table 3 and Figure 3 show the pre- and post-intervention changes in muscle mass outcomes. There were no significant changes in cross-sectional muscle area and muscle volume in the exercise group. However, the cross-sectional muscle area in the middle (*p* = 0.01) and upper levels (*p* = 0.06)

and the muscle volume of the right thigh (*p* < 0.01) declined in the control group post-intervention. Although there was a tendency to prevent loss of muscle mass in the exercise group, no significant interaction effects were detected for cross-sectional muscle area (lower level: F = 0.28, *p* = 0.60; middle level: F = 2.70, *p* = 0.11; upper level: F = 1.05, *p* = 0.31) and muscle volume (F = 1.90, *p* = 0.17). The ASMI also showed no significant group-by-time interaction (F = 1.71, *p* = 0.20).


**Table 3.** Changes in muscle mass outcomes during the 12-week intervention period.

Data presented as mean <sup>±</sup> SD. <sup>a</sup> Missing, *<sup>n</sup>* <sup>=</sup>7 (control group, *<sup>n</sup>* <sup>=</sup> 35; exercise training group, *<sup>n</sup>* <sup>=</sup> 30). <sup>b</sup> Lower, a 30-slice section from the upper edge of the patella; middle, a 60-slice section from the upper edge of the patella; upper, a 90-slice section from the upper edge of the patella (1 slice = 1.5 mm thickness).

#### **4. Discussion**

This RCT indicated that a standardized multicomponent exercise program, including progressive resistance training, improved physical function, especially chair rise and TUG performance, in community-dwelling older adults with sarcopenia or pre-sarcopenia. No adverse events related to the intervention were reported and there was a higher than 80% mean participation rate for the 12 exercise sessions.

Sarcopenia-related physical function and muscle mass decrease with age. Cross-sectional data have indicated an age-associated decline in handgrip strength and muscle mass [28]. In adults aged ≥85 years, as compared with young adults aged 20–29 years, handgrip strength was over 50% lower, and calf muscle cross-sectional area was 15% lower in women and 30% in men [28]. Longitudinal studies also showed that, in individuals aged 75 years, muscle mass decreased at a rate of 0.64%–0.7% in women and 0.8%–0.98% in men per year [29]. Strength was lost more rapidly, at a rate of 3% –4% in men and 2.5%–3% in women per year [29]. Although reduced muscle mass may be an important factor in limited mobility and strength [7], muscle strength as a marker of muscle quality could be more important in estimating mortality risk than is muscle quantity [30]. Therefore, intervention programs are needed to be highly effective at counteracting the decline in physical function, muscle mass and strength associated with ageing. The current RCT indicated useful for improvement of physical function, even for older individuals with sarcopenia.

Handgrip strength is a good predictor of poor health outcomes, including mortality [30], through mechanisms other than those leading from disease to muscle impairment. Gait speed, chair stand, and TUG tests, is also associated with future adverse outcomes including disability [31,32], hospitalization [33], and mortality [34,35]. A previous intervention study involving eight weeks of high-resistance weight training indicated significant gains in muscle strength and functional mobility among frail residents of nursing homes up to 96 years of age (mean age, 90 ± 1 years) [36]. Thus, it is never too late to start resistance exercise to improve muscle function. Multimodal training is an effective intervention to increase physical capacity among frail older individuals [37]. Integrated care including exercise, nutrition, and psychological interventions improved frailty and sarcopenia status among community-dwelling older adults, with high-intensity training yielding greater improvements [38]. Resistance training, based on the percentage of a maximum of one-repetition maximum showed significant effects on physical variables, whereas resistance training based on the rate of perceived effort presented lower effects [37]. Although a training prescription based on a one-repetition maximum practice could be better for gaining muscle, it is not realistic for determining exercise intensity in

the community setting. In the current RCT study, a multicomponent exercise program, including progressive resistance training, mainly used resistance bands, which was not a required prescription based on a one-repetition maximum practice improved physical function in older adults with loss of muscle mass, and could be useful to prevent and improve sarcopenia. However, it did not change muscle volume in older adults with sarcopenia. In order to change muscle volume, stricter exercise protocol may be needed.

A systematic review and meta-analysis that aimed to identify dose-response relationships of resistance training variables to improve muscle strength and morphology in healthy older adults indicated that 50–53 weeks of training is most effective [39]. Our multicomponent exercise program of 12 weekly sessions with a progressive protocol using a resistance band was conducted considering its feasibility in the community. Positive effects on physical function could be expected from our program for older adults with sarcopenia, but it may not be enough (e.g., intensity, frequency, and duration) for increasing muscle mass.

Nutrition may be another key element of multimodal interventions for sarcopenia [39,40]. Malnutrition and dietary patterns contribute to progressive, adverse changes in aging muscle [41,42]. Amino acids, β-hydroxyl β-methyl butyrate, energy, and vitamin D are required for muscle synthesis, so it is possible that nutritional intake influences sarcopenia [43,44]. A review suggested that the benefits of exercise could be enhanced with nutritional supplements (energy, protein, and vitamin D) [44]. On the other hand, previous reviews highlighted the importance of exercise interventions with or without nutritional supplements to improve physical function in community-dwelling older adults with sarcopenia [45]. Our program showed little evidence for increase in muscle mass in those with sarcopenia. A combination of a multicomponent exercise program and nutrition may have positive effects on both physical function and muscle mass among older adults with sarcopenia.

Several factors may mediate the associations of exercise with improvements in muscle strength and mass. For instance, genotypes (e.g., α-actinin-3 gene), endocrine, and lifestyle factors could be associated with age-related decline in muscle function [46,47]. Additional analyses are required to determine the mediation factors that support or limit the effects of exercise on muscle function.

Several limitations of this study should be noted. There was more than 80% of mean participation rate for the 12 exercise sessions. Participants were asked to exercise daily using a booklet and exercise calendar, but their adherence to this was not analyzed. Future studies would greatly benefit from the incorporation of activity monitors on the participants. Although our program mainly focused on resistance training with progressive resistance every two weeks, intensity was determined by perceived exertion, and the process was not standardized. Additionally, although other components, such as aerobic and balance exercises, were included to increase difficulty levels, these progress processes were not constant.

In conclusion, the current RCT suggests that a 12-week multicomponent exercise program with progressive resistance training generally improves physical function in community-dwelling older adults with sarcopenia or pre-sarcopenia. Multicomponent exercise could be effective at counteracting the decline in physical function for sarcopenia. However, it is unclear whether this exercise program is effective in increasing muscle mass among those with sarcopenia. Further studies might be needed to clarify the effect of treatment and prevention for the decline of muscle mass and strength related to aging and sarcopenia.

**Author Contributions:** Conceptualization, H.M.; methodology, H.M., Y.N., K.T. (Kazutoshi Tomioka), and Y.T.; formal analysis, H.M. and K.T. (Kota Tsutsumimoto); investigation, Y.N., K.T. (Kazutoshi Tomioka), Y.T., N.S., A.W., R.K., and Y.K.; resources, M.O., T.K., and T.T.; data curation, Y.N., K.T. (Kazutoshi Tomioka), Y.T., N.S., A.W., R.K., and Y.K.; writing—original draft preparation, H.M.; writing—review and editing, H.M., Y.N., K.T. (Kazutoshi Tomioka), Y.T., N.S., A.W., R.K., and K.T. (Kota Tsutsumimoto); supervision, M.O. and T.T.; project administration, H.M., M.O., T.K., and T.T.; funding acquisition, H.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by JSPS KAKENHI (Grant-in-Aid for Scientific Research [B]), Grant Number 19H03978 and the Daiwa Securities Health Foundation.

**Acknowledgments:** We thank Yukitaka Nagata, Sueharu Shimago, and Junji Ichizono, and Tamizu Chuo Hospital for their help with MRI examinations; Daisuke Hirahara, concurrent assistant professor, School Corporation Harada Gakuen, Management Planning Division, Kagoshima Medical Professional College, for his contribution to the determination of assessment methods using MRI, and Tarumizu City Office for their contributions to the study. We also thank all participants who participated in the study.

**Conflicts of Interest:** The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

### *Article* **Impact of Decorin on the Physical Function and Prognosis of Patients with Hepatocellular Carcinoma**

**Takumi Kawaguchi 1,\* , Sachiyo Yoshio <sup>2</sup> , Yuzuru Sakamoto 2,3 , Ryuki Hashida 4,5 , Shunji Koya <sup>5</sup> , Keisuke Hirota <sup>5</sup> , Dan Nakano <sup>1</sup> , Sakura Yamamura <sup>1</sup> , Takashi Niizeki <sup>1</sup> , Hiroo Matsuse 4,5 and Takuji Torimura <sup>1</sup>**


Received: 15 February 2020; Accepted: 25 March 2020; Published: 28 March 2020

**Abstract:** The outcome of patients with hepatocellular carcinoma (HCC) is still poor. Decorin is a small leucine-rich proteoglycan, which exerts antiproliferative and antiangiogenic properties in vitro. We aimed to investigate the associations of decorin with physical function and prognosis in patients with HCC. We enrolled 65 patients with HCC treated with transcatheter arterial chemoembolization (median age, 75 years; female/male, 25/40). Serum decorin levels were measured using enzyme-linked immunosorbent assays; patients were classified into the High or Low decorin groups by median levels. Associations of decorin with physical function and prognosis were evaluated by multivariate correlation and Cox regression analyses, respectively. Age and skeletal muscle indices were not significantly different between the High and Low decorin groups. In the High decorin group, the 6-min walking distance was significantly longer than the Low decorin group and was significantly correlated with serum decorin levels (*r* = 0.2927, *p* = 0.0353). In multivariate analysis, the High decorin group was independently associated with overall survival (hazard ratio 2.808, 95% confidence interval 1.016–8.018, *p* = 0.0498). In the High decorin group, overall survival rate was significantly higher than in the Low decorin group (median 732 days vs. 463 days, *p* = 0.010). In conclusion, decorin may be associated with physical function and prognosis in patients with HCC.

**Keywords:** hepatoma; myokine; decorin; walking distance; survival

### **1. Introduction**

Hepatocellular carcinoma (HCC) is a common cancer and the fourth leading cause of death due to cancer worldwide [1]. The incidence of HCC is predicted to continuously increase in both sexes and all age groups, since risk factors for HCC such as obesity, non-alcoholic steatohepatitis, and type 2 diabetes mellitus have become more prevalent worldwide [2]. In addition, the mortality rate of HCC has increased since 2000 [3], although there has been remarkable progresses in treatment for HCC, including the use of tyrosine kinase inhibitors [4]. The age-adjusted incidence and mortality rates of HCC are reported to be the highest in Eastern Asia [2]. The average 5-year survival rate is less than 15% in patients with HCC [5]. Thus, the prognosis of patients with HCC remains poor.

Skeletal muscle mass is known to be associated with the prognosis of patients with HCC [6]. Muscle atrophy is an independent factor associated with poor prognosis in patients with HCC treated with surgical resection and radiofrequency ablation [7]. Muscle atrophy is also a prognostic factor in patients with HCC treated with transarterial chemoembolization (TACE) and sorafenib [8,9]. In addition, muscle atrophy is associated with treatment tolerability and additional or subsequent therapies in patients with HCC treated with sorafenib [10]. In contrast, physical activity is associated with a reduced risk of HCC [11]. Moreover, exercise is reported to improve the prognosis of patients with HCC, regardless of changes in skeletal muscle mass [12].

Skeletal muscle is known as an endocrine organ [13]. By muscle contraction, myocytes release small peptides and cytokines, called myokines, and regulate muscle mass [13]. Myostatin is a myokine, which suppresses skeletal muscle growth and causes muscle atrophy [14]. Meanwhile, decorin is an exercise-induced myokine that suppresses muscle atrophy via inhibition of myostatin [15]. We previously reported that serum decorin levels are positively correlated with skeletal muscle mass in patients with HCC [16]. Decorin is also reported to interact with transforming growth factor-β and receptors of tyrosine kinase such as epidermal and insulin-like growth factors [17], leading to suppression of proliferation of various tumor cell lines, including HCC cell lines [18–20]. In addition, decorin is known to be expressed in various tissues including intestinal tissue, cardiac tissue, and adipose tissue and is known to regulate autophagy, inflammation, and glucose homeostasis [21–24]. Thus, accumulated evidence from basic studies suggests that decorin has an impact on the prognosis of patients with HCC. However, there has been no clinical study investigating the prognostic impact of decorin in patients with HCC.

The aim of this study was to investigate the association of serum decorin levels with physical function and prognosis in patients with HCC.

#### **2. Materials and Methods**

#### *2.1. Study Design*

This was a retrospective study to investigate the impact of serum decorin levels on the physical function and prognosis of patients with HCC.

#### *2.2. Ethics*

The study protocol conformed to the ethical guidelines of the Declaration of Helsinki and was approved by the institutional review board of Kurume University. We employed an opt-out approach to obtain informed consent from patients.

#### *2.3. Subjects*

We registered 339 consecutive patients with HCC between November 2014 and March 2018. Of these patients, 165 patients were excluded because of radiofrequency ablation (*n* = 43), hepatic arterial infusion chemotherapy (*n* = 91), tyrosine-kinase inhibitor (*n* = 23), or radiation (*n* = 8), and the remaining 174 patients with HCC who underwent TACE were selected. Of the 174 patients with HCC who underwent TACE, 105 patients were excluded because of hepatic encephalopathy (*n* = 27), HCC rupture (*n* = 17), renal failure (*n* = 7), or lack of data for physical function tests (*n* = 54). Finally, a total of 69 patients with HCC were analyzed in this study (Figure 1). We classified all patients into the High or Low decorin group per the median decorin level.

P. 3

**Figure 1.** A flow diagram of analyzed subjects.

#### *2.4. Diagnosis, Barcelona Clinic Liver Cancer (BCLC) Staging, and Treatment of HCC*

HCC was diagnosed and treated according to the guidelines for HCC of the Japan Society of Hepatology [25]. The clinical stage of HCC was evaluated using the BCLC staging system [26].

#### *2.5. Measurement of Skeletal Muscle Index (SMI) and Visceral Fat Area*

The SMI was evaluated using computed tomography (CT) images obtained at the diagnosis of HCC as previously described [27,28]. The skeletal muscle mass was measured by manual tracings on CT images, and their sum was calculated using ImageJ Version 1.50 software (National Institutes of Health, Bethesda, MD, USA) [29]. The skeletal muscle mass was evaluated by the SMI.

#### *2.6. Measurement of Physical Function*

Grip strength and the 6-min walking distance were evaluated by qualified physical therapists. Handgrip was measured on the non-dominant hand using a dynamometer (TKK5401; Takei Scientific Instruments Co., Ltd., Niigata, Japan) [6]. The 6-minute walking distance was measured by evaluating the total ambulated distance [30].

#### *2.7. Diagnosis of Sarcopenia*

The diagnosis of sarcopenia was based on the Japan Society of Hepatology diagnostic criteria for sarcopenia in patients with liver disease [6]. Patients who showed both a decrease in grip strength (the cut-off value is 26 kg for men and 18 kg for women) and a decrease in skeletal muscle mass (the cut-off value of SMI is 42 cm<sup>2</sup> /m<sup>2</sup> for men and 38 cm<sup>2</sup> /m<sup>2</sup> for women) were diagnosed with sarcopenia. The other patients were classified as non-sarcopenia [6].

#### *2.8. Biochemical Tests*

γ Blood samples were obtained at the baseline in the early morning after an overnight fast. The blood biochemical tests performed were for serum levels of alpha-fetoprotein, des-γ-carboxy prothrombin, liver function tests, renal function tests, total cholesterol, creatine kinase, and hemoglobin A1c. We also measured the complete blood cell count.

#### *2.9. Measurement of Serum Levels of Myostatin, FGF-21 and Decorin*

Serum levels of myostatin, FGF-21, and decorin were measured using a Myostatin Quantikine enzyme-linked immunosorbent assay (ELISA) Kit (R&D Systems, Inc., Minneapolis, MN, USA), Human FGF-21 ELISA Kit (BioVendor—Laboratorni medicina a.s., Brno, Czech Republic), and Human Decorin ELISA Kit (Abcam plc., Cambridge, UK) according to the manufacturers' instructions, respectively.

#### *2.10. Follow-Up and Definition of Survival Term*

After treatment with TACE, patients were followed up until death or the study censor date through routine physical examinations, biochemical tests, and abdominal imaging including ultrasonography, CT, or magnetic resonance imaging according to the HCC guidelines of the Japan Society of Hepatology [25]. The median observational period was 617 days (range, 52–2068 days). The survival term was defined as the period from the diagnosis of HCC to death or the study censor date.

#### *2.11. Statistical Analysis*

Data are expressed as the median (interquartile range), range, or number. The differences between the High and Low decorin groups were analyzed using Wilcoxon rank sum tests. Factors correlated with serum decorin levels were evaluated by pairwise correlations [31]. In addition, independent factors associated with survival were analyzed using Cox regression analysis, as previously described [27]. The overall survival in the High and Low decorin groups was estimated using the Kaplan–Meier method, and differences in survival between the groups were analyzed using the log-rank test. All the statistical analyses were performed using JMP Pro® 14 (SAS Institute Inc., Cary, NC, USA). Values of *p* < 0.05 were considered to indicate statistically significant differences.

#### **3. Results**

#### *3.1. Patient Characteristics*

The patient characteristics are summarized in Table 1. There was no significant difference in age and body mass index. The prevalence of men was significantly higher in the High decorin group than that in the Low decorin group. There was no significant difference in the hospitalization period between the two groups.

In the High decorin group, the prevalence of sarcopenia was significantly lower than that in the Low decorin group. Although no significant differences were noted in the SMI and serum creatine kinase level between the two groups, the 6-min walking distance in the High decorin group was significantly longer than that in the Low decorin group (Table 1).

Although there was no significant difference in the serum fibroblast growth factor (FGF)-21 level between the two groups, the serum level of myostatin was significantly higher in the High decorin group than that in the Low decorin group (Table 1).

There was no significant difference in the BCLC classification between the High and Low decorin groups. No significant difference in the serum alpha-fetoprotein level was also observed between the two groups; however, in the High decorin group, the serum des-γ-carboxy prothrombin level was significantly lower than that in the Low decorin group (Table 1).

There was no significant difference in the prevalence of Child–Pugh class B and use of branched-chain amino acid supplementation between the two groups. Serum levels of aspartate aminotransferase, alanine aminotransferase, and estimated glomerular filtration rate were significantly higher in the High decorin group than those in the Low decorin group. In the High decorin group, serum levels of blood urea nitrogen, creatinine, and triglycerides and the hemoglobin A1c value were significantly lower than those in the Low decorin group (Table 1).




aspartate aminotransferase; BCAA, branched-chain amino acid; BCLC, Barcelona Clinic Liver Cancer; DCP, des-γ-carboxy prothrombin; eGFR, estimated glomerularfibroblastgrowthfactor-21;GGT,gamma-glutamyltranspeptidase;HbA1c,hemoglobinA1c;N/A,notapplicable

#### *3.2. Multivariate Correlation Analysis Between Serum Decorin Levels and Each Variable*

No significant correlation was seen between serum decorin levels and age, body mass index, grip strength, SMI, levels of alpha-fetoprotein, albumin, total bilirubin, creatine kinase, hemoglobin A1c, and estimated glomerular filtration rate. Serum decorin levels showed a significant negative correlation with serum des-γ-carboxy prothrombin levels. Serum decorin levels demonstrated a significant positive correlation between the 6-min walking distance and serum myostatin levels (Table 2).


**Table 2.** Multivariate correlation analysis between serum decorin levels and each variable.

Abbreviations: FGF-21, fibroblast growth factor-21; AFP, alpha-fetoprotein; DCP, des-γ-carboxy prothrombin; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; GGT, gamma-glutamyl transpeptidase; eGFR, estimated glomerular filtration rate; HbA1c, hemoglobin A1c.

#### *3.3. Independent Factors Associated with Survival*

We examined independent factors associated with survival and found that high decorin levels were identified as an independent factor of better overall survival. Meanwhile, the BCLC stage and Child–Pugh class were not identified as independent factors associated with overall survival (Table 3).


**Table 3.** Multivariate Cox regression analysis for overall survival.

Abbreviations: BCLC, Barcelona Clinic Liver Cancer.

#### *3.4. Kaplan–Meier Analysis for Survival*

In the High decorin group, the overall survival rate was significantly higher compared to that in the Low decorin group (median 732 days vs. 463 days; log-rank test *p* = 0.0498) (Figure 2A). In the subgroup analysis of BCLC stage B, the difference in overall survival rates between the High and Low decorin groups became more significant than that in the analysis in all subjects (BCLC stages A and B) (Figure 2B).

**Figure 2.** Kaplan–Meier analysis between the High decorin and Low decorin groups. (**A**) All patients; (**B**) Patients with BCLC stage B HCC. BCLC, Barcelona Clinic Liver Cancer; HCC, hepatocellular carcinoma.

#### **4. Discussion**

In this study, we demonstrated that serum decorin levels were positively correlated with the 6-min walking distance, an index of cardiopulmonary function in patients with HCC. In addition, we found that serum decorin levels were an independent prognostic factor in patients with HCC. Although more research is needed and our data are preliminary in essence, these data suggest that decorin may be associated with physical function and prognosis in patients with HCC.

TACE is a standard treatment for intermediate-stage HCC [26,32]. In this study, we enrolled patients with HCC treated with TACE, and the median survival period was 617 days, which is comparable to that reported previously [26,33]. The prognosis of patients with HCC is dependent on the BCLC stage [26]. However, the BCLC stage was not identified as an independent prognostic factor in this study, and the reason for this remains unclear. However, all enrolled patients with HCC were treated with TACE, and patients with the BCLC stage B accounted for about 90% of the enrolled patients. Therefore, the narrow distribution of the BCLC stage may be a possible explanation.

ƙ Although myostatin and FGF-21 are myokines, the levels of these myokines were not identified as independent prognostic factors in patients with HCC. Nishikawa et al. reported that elevated serum myostatin levels are associated with worse survival in patients with liver cirrhosis [34]. Hyperammonemia has been reported to transcriptionally upregulate myostatin through nuclear transport of p65 nuclear factor-κB, resulting in sarcopenia and poor prognosis [35]. Meanwhile, patients with hepatic encephalopathy (West Haven criteria grade II–IV) were excluded, and the prevalence of hyperammonemia was thought to be low in this study. Therefore, myostatin may not be identified as a prognostic factor. Deficiency of FGF-21 is reported to promote HCC in mice receiving a long-term obesogenic diet [36]. Long-term administration of FGF-21 prevents chemically induced hepatocarcinogenesis in mice [37]. However, FGF-21 is known to be expressed in several tissues, including those of the liver, fat, and pancreas [38]. Serum FGF-21 levels are affected by various tissues expressing FGF-21, and, therefore, FGF-21 was not identified as an independent prognostic factor in patients with HCC.

Serum decorin levels were positively correlated with the 6-min walking distance, an index of cardiopulmonary function in patients with HCC. Overexpression of decorin is reported to ameliorate diabetic cardiomyopathy and cardiac function in rats [39]. N-terminal cleavage of decorin confers an inhibitory effect against myostatin, suppressing the atrophy of cardiomyocytes [40]. In fact, serum decorin level was positively correlated with serum myostatin level in this study. One would think that decorin may be up regulated to suppress muscle atrophy in response to an increase in serum myostatin level. In addition, C-terminal truncation of decorin interacts with the connective tissue growth factor, leading to suppression of myocardial fibrosis through down-regulation of cardiac extracellular matrix production [40]. Furthermore, Kwon et al. reported that decorin causes macrophage polarization via cluster of differentiation-44, resulting in an amelioration of pulmonary function in a rat model of hypertoxic lung damage [41]. These previous basic studies, along with our results, may suggest that decorin may be associated with cardiopulmonary function in patients with HCC (Figure 3). However, the correlation between serum decorin level and the 6-min walking distance could not lead to the conclusion that the high decorin level is a cause of high cardiovascular fitness, in such a small number of subjects.

β β α β β β β α α **Figure 3.** A scheme for the proposed hypothesis of this study. Decorin is expressed in various tissues including skeletal muscle, heart, intestine, and adipocytes. In this study, it remains unclear where decorin comes from. Decorin may be associated with cardiopulmonary function, because decorin suppresses the atrophy of cardiomyocytes, myocardial fibrosis, and causes macrophage polarization. In addition, decorin may be associated with prognosis of patients with HCC, because decorin downregulates transforming growth factor-β1, epidermal growth factor receptor, glycogen synthase kinase 3β, and extracellular signal-regulated kinase 1/2, G2/M arrest through phosphorylation of cyclin-dependent kinase 1, downregulation of vascular endothelial growth factor A, hypoxia-inducible factor 1-α, and hepatocyte growth factor. Abbreviations: TGF β, transforming growth factor-β1; EGF, epidermal growth factor receptor; GSK3β, glycogen synthase kinase 3β; and ERK, extracellular signal-regulated kinase; VEGF, vascular endothelial growth factor; HIF-1α, hypoxia-inducible factor 1-α; HGF, hepatocyte growth factor.

In this study, we first examined the impact of the serum decorin level in patients with HCC and found that serum decorin levels were identified as an independent prognostic factor in patients with HCC. Moreover, in the stratification analysis according to the BCLC stage, the prognostic impact of decorin was more evident in patients with HCC with the BCLC stage B. Horváth et al. reported that genetic ablation of decorin leads to enhanced hepatocarcinogenesis compared to that in wild-type animals [42]. Meanwhile, recombinant human decorin inhibits the proliferation of HepG2 cells [43,44]. Several mechanisms for decorin-induced inhibition of cell proliferation have been reported. Decorin is reported to reduce the secretion of transforming growth factor-β1 in HCC cell

lines [20]. Decorin is also reported to downregulate the phosphorylation of epidermal growth factor receptor, glycogen synthase kinase 3β, and extracellular signal-regulated kinase 1/2 [20]. In addition, decorin suppresses the ATR/Chk1/Wee1 axis, leading to inhibition of the cell cycle in the G2/M phase via phosphorylation of cyclin-dependent kinase 1 [20]. Moreover, decorin is known to decrease the expression of pro-angiogenic factors, vascular endothelial growth factor A, and hypoxia-inducible factor 1-α, resulting in downregulation of the hepatocyte growth factor and epidermal growth factor receptor signaling axes [45]. In fact, the serum decorin level was negatively correlated with the serum des-γ-carboxy prothrombin level, which is a tumor maker for HCC in this study. Thus, decorin may suppress the proliferation of HCC through direct and indirect tumor inhibitory effects and may be associated with prognosis in patients with HCC (Figure 3). However, decorin is known to be expressed not only in skeletal muscle [15], but also in various tissues including intestinal tissue, cardiac tissue, and adipose tissue [21–24]. Accordingly, it remains unclear where decorin comes from in the present study (Figure 3). In addition, we have to be cautious of the interpretation of our data. Expression of decorin is recently reported to be seen in the tumor cell such as glioblastoma and is negatively associated with the overall survival rate of patients with glioblastoma multiforme [46]. Thus, further research is required to investigate the expression of decorin in HCC tissue and a causal relationship between decorin and prognosis of the patients with HCC.

Limitations of this study are the following: First, this was a retrospective study conducted in a single center. Second, the number of enrolled subjects is very limited to examine independent prognostic factors. Third, we enrolled patients with HCC treated with TACE. It remains unclear if serum decorin levels have a prognostic impact in patients with HCC treated with hepatic resection or tyrosine kinase inhibitors. Fourth, no patient underwent liver transplantation during the observation period, suggesting the selection bias. Thus, a multicenter prospective cohort study should be conducted with various HCC stages and treatments for HCC including liver transplantation.

#### **5. Conclusions**

In conclusion, we demonstrated that serum decorin levels were positively correlated with cardiopulmonary function in patients with HCC. In addition, serum decorin levels were an independent prognostic factor in patients with HCC. Although more research is needed and our data are preliminary in essence, the results of this study may suggest that decorin may be associated with physical function and prognosis in patients with HCC.

**Author Contributions:** Author Contributions: T.K., S.Y. (Sachiyo Yoshio), and R.H. participated in the study conception and design, data acquisition and interpretation, and manuscript drafting. Y.S. participated in data analysis and manuscript drafting. S.K., K.H., D.N., S.Y. (Sakura Yamamura), and T.N. participated in data acquisition and interpretation and manuscript drafting. H.M. and T.T. participated in the study conception and design, interpretation, and critical revision. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was supported by the Program for Basic and Clinical Research on Hepatitis (AMED) under JP19fk0210045.

**Acknowledgments:** We would like to thank Editage for English language editing.

**Conflicts of Interest:** T.K. received lecture fees from MSD K.K., Mitsubishi Tanabe Pharma Corporation and Otsuka Pharmaceutical Co., Ltd. The other authors have no conflicts of interest.

#### **References**


© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

MDPI St. Alban-Anlage 66 4052 Basel Switzerland Tel. +41 61 683 77 34 Fax +41 61 302 89 18 www.mdpi.com

*Journal of Clinical Medicine* Editorial Office E-mail: jcm@mdpi.com www.mdpi.com/journal/jcm

MDPI St. Alban-Anlage 66 4052 Basel Switzerland

Tel: +41 61 683 77 34 Fax: +41 61 302 89 18

www.mdpi.com ISBN 978-3-0365-1535-9