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SARCOPENIA IN PRIMARY CARE: SCREENING, DIAGNOSIS, MANAGEMENT

 

S. Crosignani1, C. Sedini1, R. Calvani2, E. Marzetti2, M. Cesari3

 
1. Fellowship in Geriatrics and Gerontology, University of Milan, Milan, Italy; 2. Fondazione Policlinico Universitario “Agostino Gemelli” IRCCS, Catholic University of the Sacred Heart Rome, Italy; 3. IRCCS Istituti Clinici Scientifici Maugeri, University of Milan, Milan, Italy
Corresponding author: Silvia Crosignani, MD, Email: silvia.crosignani@unimi.it

J Frailty Aging 2020;in press
Published online December 7, 2020, http://dx.doi.org/10.14283/jfa.2020.63


Abstract

Detection of sarcopenia in primary care is a first and essential step in community-dwelling older adults before implementing preventive interventions against the onset of disabling conditions. In fact, leaving this condition undiagnosed and untreated can impact on the individual’s quality of life and function, as well as on healthcare costs. This article summarizes the many instruments today available for promoting an earlier and prompter detection of sarcopenia in primary care, combining insights about its clinical management. Primary care physicians may indeed play a crucial role in the identification of individuals exposed to the risk of sarcopenia or already presenting this condition. To confirm the suspected diagnosis, several possible techniques may be advocated, but it is important that strategies are specifically calibrated to the needs, priorities and resources of the setting where the evaluation is conducted. To tackle sarcopenia, nutritional counselling and physical activity programs are today the two main interventions to be proposed. Multicomponent and personalized exercise programs can (and should) be prescribed by primary care physicians, taking advantage of validated programs ad hoc designed for this purpose (e.g., the Vivifrail protocol). It is possible that, in the next future, new pharmacological treatments may become available for tackling the skeletal muscle decline. These will probably find application in those individuals non-responding to lifestyle interventions.

Key words: Skeletal muscle, aging, geriatrics, physical function, muscle strength.


 

Introduction

“Sarcopenia” is a term referred to the progressive loss of skeletal muscle mass typically occurring with advancing age, as defined by Irwin Rosenberg in 1989 (1). Since then, the term has been used to more broadly embrace the age-related skeletal muscle decline, including both decrease in mass as well as reduction in strength and performance. To date, several definitions of sarcopenia have been proposed in the literature, and different consensus articles have tried to operationally frame this condition. Unfortunately, despite the fact that sarcopenia has even received a specific ICD-10 code in October 2016 (2), there is still no agreement in the scientific community about the gold standard definition to adopt for capturing this condition (3). Table 1 presents the most widely used definitions of sarcopenia currently available in the literature.

Table 1
Main definitions of sarcopenia

 

Sarcopenia still represents an underdiagnosed condition in daily practice, leaving untreated many cases amenable of interventions. Given the aging of the population, it is important that primary care physicians become familiar with the management of this condition for multiple reasons:
1) Detecting sarcopenia should be part of the routine visit due to the simplicity of the necessary tools and for the limited time required;
2) Sarcopenia is considered a reversible condition and can be contrasted by correct nutrition advices and personalized physical activity programs (4, 5);
3) Interventions directed against geriatric conditions, such as sarcopenia, are usually developed with long-term objectives (6), thus likely to involve the co-management by the primary care physician;
4) The management of a clinical condition, especially at advanced age, is strongly facilitated when the primary care physician (the one who best knows the clinical characteristics and behaviours of the patient) plays an active role;
5) Tackling sarcopenia is of primary importance in the community, where the vicious cycle of disability may still be amenable of reversion;
6) Recognizing sarcopenia in primary care may improve the design of the optimal care plan for the older person.

The present article is aimed at summarizing available evidence about the diagnosis and therapeutic process that can be activated for sarcopenia in primary care. The available diagnostic tools to recognize and quantify sarcopenia will be critically discussed. In particular, it will be considered that the operational definition of sarcopenia in primary care should be balanced to the limited availability of resources and time in this specific setting.

 

Prevalence, clinical relevance and costs

According to the World Health Organization (WHO), in 2050 there will be at least 2 billion persons aged 65 years or older, compared to the current 600 million. The increasing life expectancy is a worldwide demographic phenomenon, parallel to the growing number of persons affected by age-related chronic conditions (including sarcopenia).
In the absence of a gold standard for capturing sarcopenia, the estimate of its prevalence remains quite variable. Furthermore, the prevalence of sarcopenia is also highly influenced by the studied population and the setting where the condition is looked for, thus limiting the availability of single and reliable estimates. Nevertheless, a relatively robust evaluation of the phenomenon sets the prevalence of sarcopenia to be between 8.4% and 27.6% in community-dwelling older persons (7, 8), 14-33% in long-term care residents and 10% in acute hospital care population (9).
Sarcopenia is more likely to be present in men than in women and tends to increase with advancing age. Asians, persons with low body mass index, and those with low education represent other groups of people at higher risk of sarcopenia (7).
Sarcopenia has been associated with many negative health-related outcomes, including disability, poor physical function, falls, fractures, loss of independence, hospitalizations, institutionalization, and mortality. In patients with several comorbidities and clinical conditions (e.g., patients with cancer or undergoing surgery), sarcopenia has shown to represent a negative prognostic factor (10, 11).
Analyses conducted on Third National Health and Nutrition Examination Survey (NHANES III) database have calculated the direct costs of sarcopenia. Sarcopenia was found to cost about$18,5 billion ($10.8 billion in men, $7.7 billion in women) per year in the United States, and it represented about 1.5% of total direct health care costs calculated in the year 2000 (12). Reducing the prevalence of sarcopenia by 10% would result in about $1.1 billion savings per year. And this without considering the indirect costs of sarcopenia, such as the loss of productivity for the individual as well as for the eventual caregivers(12).Another example of how burdensome is sarcopenia for public health is brought by a Portuguese study showing that sarcopenia is independently related to hospitalization costs, independently of age. Sarcopenia was responsible for adding €884 per patient (95% confidence interval [95%CI] €295-€1,476) to hospital care costs, that represents a 58.5% increase. Again, these figures are likely underestimating the economic burden of sarcopenia because not taking into account the indirect costs (13).
In order to adequately tackle sarcopenia and prevent its detrimental consequences (for both the individual and the healthcare system), it is mandatory to design and implement an effective plan of action. In fact, it is important to preventively track sarcopenia when it is still reversible, and before its vicious cycle might cause the onset of frailty and disability.In this context, it is noteworthy that not everyone with sarcopenia is disable, but the condition substantially increases the risk of disability (14). Not surprisingly, sarcopenia is frequently considered as a condition to target for avoiding the most negative consequences of the disabling process. At the same time, the positioning of sarcopenia at the initial phases of physical dysfunction automatically indicates this as a condition of special interest for primary care professionals. In other words, the detection of sarcopenia (or, at least, the suspicion of it) in primary care might promote the implementation of successful interventions when the person is still independently living in the community.

 

Screening

It is recommended that adults aged 65 years and older should be screened annually for sarcopenia, or after the occurrence of major health events (falls, hospitalization).
It is also advisable screening older adults on the occasion of the first consultation or, for instance, at annual health check-up or flu vaccination appointments (15).
For the screening of sarcopenia in primary care, several instruments and methodologies have been developed over the years. It is generally recommended that the presence of sarcopenia should be suspected in every individual aged 65 years or older, presenting signs or symptoms suggestive of skeletal muscle impairment (3). A recent consensus paper promoting the identification and management of sarcopenia in primary care has proposed the so-called “Red Flag Method”(3) (Table 2). The purpose of this method is to generate alerts about those physical manifestations typically caused by sarcopenia that can be 1) reported by the subject, or 2) evaluated by the physician during the clinical assessment. In other words, the Red Flag Method may represent a sort of checklist for supporting the physician at the identification of several neglected signs, symptoms and conditions behind which sarcopenia might be hidden(3). The pedagogical value of the method should also be acknowledged. In fact, healthcare professionals may find in it a way for being trained at the clinical manifestation of sarcopenia, becoming more familiar with it, and introducing the process in the daily routine.

Table 2
The“red flag” method, SARC-F, and other instruments for the assessment of sarcopenia in the primary care setting

BIA: Body Impedance Analysis; DXA: Dual-energy X-ray Absorptiometry; CT: computed tomography; MRI: magnetic resonance imaging; SPPB test: Short Physical Performance Battery test; TUG: Time Up and Go.

 

Alternatives to formal/structured assessments might also be found in actions made by the individual during the clinical contact. For example, hints about the possible presence of sarcopenia might be provided by the strength of the individual’s handshake, his/her walking speed from the waiting room to the office, or observing how the person sits down and stands up from the chair.
If the Red Flag Method is based on a relatively long list of items to consider in the identification of possible sarcopenia, John Morley recently developed an ad hoc instrument (i.e., the SARC-F questionnaire) for a more rapid screening of the condition(16). SARC-F is the acronym of Strength, Assistance in walking, Rise from a chair, Climb stairs, and Falls. Each of these items receives a score ranging between 0 (absence of the sign) and 2 (inability or severe issue). A total score equal to or higher than 4 points is predictive of sarcopenia and poor health-related outcomes. The SARC-F can be used to identify individuals in the need of a more detailed and careful assessment of sarcopenia, and potentially lead to a more in-depth analysis of the case through the comprehensive geriatric assessment. Interestingly, in the revised version of the European recommendations for the definition and diagnosis of sarcopenia, designed by the European Working Group on Sarcopenia in Older People (EWGSOP), the use of SARC-F is suggested for the early identification of individuals amenable of further evaluation (17). This choice is motivated by the low sensitivity and high specificity of the instrument (17, 18).
Another opportunity for promoting the inclusion of the sarcopenia assessment in primary care can be found in a wider use of anthropometry. Although they would be useful to assess the body composition, the most commonly considered imaging methods might be unfeasible in primary care. Anthropometry (i.e., the measurement of body mass index, waist circumference, calf circumference, mid-upper arm circumference, and/or skinfold thickness) may provide easily applicable, inexpensive, and non-invasive techniques for identifying individuals at risk of presenting low muscle mass (19, 20). Recently, the Yubi-Wakka (finger-ring)test has also been proposed in this context. This is a simple self-screening method to quickly assess sarcopenia, comparing the calf circumference with the ring generated by the individual’s fingers (21).Table 2 lists several methods to be considered for the screening of sarcopenia in primary care.

 

Diagnosis

As mentioned, a gold standard definition to diagnose sarcopenia is today not yet available. In general, the available recommendations coming from different panels of experts and task forces tend to indicate the need of combining a quantitative dimension (capturing the skeletal muscle mass) and a qualitative one (assessing the skeletal muscle function). Whereas the assessments of skeletal muscle strength and/or physical performance are relatively easy to be conducted, the body composition evaluation might be challenging in the primary care setting. In fact, general practitioners may not have easy/immediate access to the suggested methodologies for measuring the skeletal muscle mass, or (at best) may have to rely on suboptimal techniques. For this reason, the accurate diagnosis of sarcopenia is likely to require the referral to specialized centres, where the dual energy X-ray absorptiometry (DXA) or other (more sophisticated) techniques (e.g., magnetic resonance imaging or computerized tomography) are available. At best, the quantification of the skeletal muscle mass in primary care might be estimated using the bioelectrical impedance analysis (BIA). This technique is inexpensive, easy to use, and readily reproducible, although its results might be inaccurate, especially in the presence of certain clinical conditions (e.g., in the presence of fluid retention).
Nevertheless, a lot can still be done in primary care to detect the sarcopenia condition. The identification of individuals with sarcopenia might also start by measuring some neglected signs or symptoms of muscular poor health, for example by formally and routinely testing muscle strength/performance. In this context, the routine adoption of the handgrip strength is widely recommended and relatively easy to implement in primary care and represents a cornerstone parameter for the diagnosis of sarcopenia (22–24). In case a dynamometer is not available, the Chair Stand Test can be a valid and reliable alternative for measuring the muscle strength (17).
It is likely that, in the next future, novel methodologies will be developed for supporting Physician to diagnose sarcopenia. One of themost promising ones is represented by the deuterated creatine (D3-creatine) dilution method, which is able to provide a direct quantification of the individual’s muscle mass via the ingestion of deuterium-marked creatine and is the only technique providing a direct and unbiased estimate of muscle mass.
Although its use is currently limited to the research setting(19), this method has relevant potential for diffusion in primary care because 1) based on the simple administration of a pill and a urine analysis (to be performed after 24-48 hours), and 2) overcoming the need of the above-mentioned diagnostic tools for body composition assessment.

 

Management

Primary care physicians may play a crucial role in the identification of individuals exposed to the risk of sarcopenia or already presenting this condition. They may preventively act providing recommendations for managing reversible risk factors (e.g., sedentary behavior, unhealthy diet) and eventually referring them to specialists for further evaluation.
To date, no pharmacological agent is available for the treatment of sarcopenia, but several molecules (at different stages of development) are in the pipelines of pharmaceutical industries. Thus, physical activity and nutritional interventions currently represent the basis of the clinical management of sarcopenia(25,26). Unfortunately, there is still a general lack of knowledge among healthcare professionals for correctly prescribing personalized interventions of physical activity and/or healthy diet.

Physical activity

The design ofa person-tailored physical activity program for tackling sarcopenia is not easy, especially if considering 1) the clinical complexity of older persons presenting this condition, and 2) the lack of adequate training that healthcare professionals may receive for this task during the curriculum of traditional study. Nevertheless, the beneficial effects that a physical exercise program may exert in frail and/or sarcopenic individuals is very well documented (27).
In general, multicomponent/combined exercise programs including aerobic activities, resistance training, and flexibility exercises are recommended. These should be proposed by primary care physicians to frail and/or sedentary community-dwelling persons as part of clinical routine (15). In this context, the material produced by VIVIFRAIL project is important to be mentioned (28). VIVIFRAIL was designed to provide support to primary care physicians in the prescription of personalized programs of physical activity. The program is based on a preliminary assessment of the individual’s physical performance, muscle strength, balance, and risk of falls. The results of such evaluation are then used to design an intervention that is tailored to the individual’s capacities and deficits. Importantly, VIVIFRAIL is designed for empowering the individual at monitoring his/her progresses (29). The VIVIFRAIL material is available at the project website (www.vivifrail.eu), and an app has also been developed for supporting the individual and the healthcare professionals.
Another project to be mentioned for its potential of reshaping the management of sarcopenia is “The Sarcopenia and Physical fRailty IN older people: multi-componenT Treatment strategies” (SPRINTT) study(30). This project, funded by the Innovative Medicines Initiative (IMI), is aimed to developing an operational definition of sarcopenia that might be acceptable by regulatory agencies. The project includes a randomized control trial designed to test the effects of a multidomain lifestyle intervention (mainly based on physical activity and nutritional counselling) on a condition combining physical frailty and sarcopenia. Interestingly, the target condition was theoretically framed in order to mirror the nosological conditions that are traditionally object of observation by regulatory agencies. The developed operational definition has been preliminarily endorsed by the European Medicines Agency before the beginning of the SPRINTT randomized controlled trial. At the end of the trial, investigators will be in the position of 1) estimating the prevalence of the novel condition in the general population, 2) ascertain the reversibility of the condition after implementation of lifestyle changes promoting healthy ageing, and 3) identify a subgroup of individuals resistant to the beneficial effects of physical activity and healthy diet. In particular, this latter point is of special interest because paving the way towards the profiling of future candidates to pharmacological interventions against sarcopenia (31).

Nutrition

Malnutrition is a condition due to a protein or other nutrient imbalance, responsible for negative effects on body composition, physical function, and clinical outcome. It plays a key role in the pathogenesis of sarcopenia and fragility. It is necessary to recognize malnutrition early in older adults to plan nutritional programs aimed at improving the outcome (32).
In hospital settings Nutrition Risk Screening-2002 (NRS-2002) or Malnutrition Universal Screening Tool (MUST) are used for the screening of malnutrition whereas Mini Nutritional Assessment (MNA) is considered the gold standard for the older adults hospitalized or in an outpatient setting. In the subject at risk of malnutrition, the evaluation of the nutritional status must be carried out.
These screening tools help to have a patient-centered approach, provide adequate nutritional advice, and monitoring nutritional status over time (33, 34).
An example of malnutrition prevention is the “Health Enhancement Program (HEP)”, a randomized trial with robust results. After an initial assessment conducted by a trained staff of each participant’s health and functional status, a personalized plan was carried out to counteract disability risk factors. The program consists in motivational strategies to promote behavioral changes in depression, poor nutrition, and a sedentary lifestyle. At one year follow up, compared with enrollment, a reduction of risk factors was registered (35).
An attempt of intervention in frail older adults in a clinical setting is the program of the Geriatric Frailty Clinic (G. F. C.) at the Gerontopole of Toulouse. Older adults, considered as frail by their General Practitioner, underwent a multidisciplinary evaluation at the G.F.C where the team members proposed a Personalized Prevention Plan (PPP); in case of malnutrition, detected by the MNA, a nutritionist was asked for improve dietary intake with specific recommendations. A follow-up, consisted of a nurse call after one month and three months, was organized to determine the intervention’s efficacy. After one year the Geriatrician reassessed the patient’s improvements with a multidisciplinary evaluation (36).
Recently, two consensus papers (promoted by the European Society for Clinical Nutrition and Metabolism and the PROT-AGE study group) agreed that people aged 65 years or older require a higher intake of proteins compared to what usually recommended for activating muscle protein synthesis and maintaining muscle health. Therefore, both groups recommended the assumption of at least 1–1.2 g of proteins/kg/day in older persons, pushing even higher this minimum threshold in the presence of catabolic or muscle wasting conditions (37, 38).
About the quality of proteins, essential amino acids (EAAs; in particular leucine) are recognized as providing an important anabolic stimulus. In fact, leucine is able to increase muscle protein synthesis in older people, as also confirmed in a recent meta-analysis. In fact, its consumption has been found to be directly correlated with muscle mass in healthy older people (39).
β-hydroxy β-methylbutyrate (HMB) is one of the metabolites of leucine that is able to exert anabolic effects. HMB is frequently used by athletes to improve their physical performance and has also showed promising results in improving muscle mass and strength in older adults. When applied to bed resting older people, HMB stimulated muscle mass preservation. HBM supplementation combined with exercise seems to promote the regenerative capacity of skeletal muscles (25).
For what concerns vitamin D, its supplementation is surely useful for correcting states of insufficiency or deficiency (40, 41). Nevertheless, no evidence supports its use in individuals with normal vitamin D concentrations for improving muscle health.

Drugs

No drugs are currently registered for use in the treatment of sarcopenia, and no pharmacological intervention can be accepted as first-line therapy of sarcopenia (15). However, several new molecules are currently under study at various stages of development. It is noteworthy the special interest devoted by regulatory agencies in this field. Both the Food and Drugs Administration and the European Medicines Agency are paving the way for structuring pharmacological research on this topic.
Despite the urgency of the problem, the development of pharmaceutical therapies for sarcopenia and frailty has lagged, in part because of the lack of consensus definitions for the two conditions. In 2015,an experts’ group gathered during the International Conference on Frailty and Sarcopenia Research (ICSFR) to discuss challenges related to drugs designed to the target the biology of frailty and sarcopenia (8).
Based on the available evidence, myostatin antagonists, like Bimagrumab, may be promising candidates to treat people with low lean muscle mass, in particular people older than 70 years. Bimagrumab is a monoclonal antibody that blocks the binding of myostatin to activin, thus blocking its negative regulation of muscle growth (42). Young men treated with a single dose of Bimagrumab may experience an increase in muscle mass similar to that induced by 12 week of high-intensity resistance training(43,44), while sedentary adults may receive a benefit equivalent to 9 months of jogging 12-20 miles per week (45).
Researchers are also focused on selective androgen receptor modulators (SARMs). These are a class of androgen receptor ligands that increase low lean muscle mass by binding to the androgen receptor in muscles. Different molecules have already undergone phase I, II and III trials, but at the moment longer studies are required to demonstrate the long-term safety and the efficacy of these drugs (8).
Inflammatory modulators, such as those acting on the tumour necrosis factor-α (TNFα) and interleukin-1 (IL1), are also under study. Systemic inflammation and the increasing of TNFα and IL1 in blood lead to muscle atrophy (46). Inflammatory modulators could limit the reduction of skeletal muscle by reducing pro-inflammatory cytokines.

 

Conclusions

Sarcopenia is the age-related progressive decline of skeletal muscle. It is a common age-related condition, and has a relevant impact on the person’s quality of life and functioning, as well as on healthcare costs.
Primary care physicians may play a pivotal role in the identification of the risk of sarcopenia in the aged population. Indeed, the primary care physician may detect the early manifestations of this condition and lead to its fast diagnosis and care. In this framework, multiple instruments have been developed for promoting the detection of sarcopenia in primary care. Once sarcopenia is identified, a comprehensive assessment of the individual may lead to person-tailored interventions based on nutritional counselling and physical activity programs. In the next future, the availability of pharmacological therapies could be able to prevent the skeletal muscle decline in those individuals resistant to the benefits of healthy lifestyle prescriptions.

 

Conflicts of Interest: Matteo Cesari received honoraria from Nestlé for presentations at scientific meetings and as member of scientific advisory boards. No other conflict of interest declared by the Authors.

 

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ASSOCIATION OF MUSCLE STRENGTH AND GAIT SPEED WITH CROSS-SECTIONAL MUSCLE AREA DETERMINED BY MID-THIGH COMPUTED TOMOGRAPHY – A COMPARISON WITH SKELETAL MUSCLE MASS MEASURED BY DUAL-ENERGY X-RAY ABSORPTIOMETRY

 

K. Tsukasaki1,6, Y. Matsui1,7, H. Arai2, A. Harada1, M. Tomida3, M. Takemura1, R. Otsuka3, F. Ando3,4, H. Shimokata3,5

 

1. Department of Orthopedic Surgery, National Center for Geriatrics and Gerontology, Obu, Japan; 2. National Center for Geriatrics and Gerontology, Obu, Japan; 3. Section of NILS-LSA, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, Obu, Japan; 4. Faculty of Health and Medical Science, Aichi Shukutoku University, Nagakute, Japan; 5. Graduate School of Nutritional Sciences, Nagoya University of Arts and Sciences, Nisshin, Japan; 6. Hokuto Hospital, Japan; 7. Center for Frailty and Locomotive syndrome, National Center for Geriatrics and Gerontology, Obu, Japan. Corresponding author: Yasumoto Matsui, Center for Frailty and Locomotive syndrome, National Center for Geriatrics and Gerontology, 7-430. Morioka-cho, Obu, Aichi, Japan, e-mail address: matsui@ncgg.go.jp, telephone 81-522-046-2311, fax numbers:81-562-44-8518

J Frailty Aging 2020;9(2)82-89
Published online March 30, 2020, http://dx.doi.org/10.14283/jfa.2020.16

 


Abstract

Background: Muscle mass is often mentioned not to reflect muscle strength. For muscle mass assessment skeletal muscle index (SMI) is often used. We have reported that dual-energy X-ray absorptiometry (DXA)-derived SMI does not change with age in women, whereas the cross-sectional muscle area (CSMA) derived from computed tomography (CT) does. Objectives: The present study aimed to compare CT and DXA for the assessment of muscle tissue. Design & Setting: Cross-sectional study in the local residents. Participants: A total of 1818 subjects (age 40-89 years) randomly selected from community dwellers underwent CT examination of the right mid-thigh to measure the cross-sectional muscle area (CSMA). Skeletal muscle mass (SMM) was measured by DXA. The subjects performed physical function tests such as grip strength, knee extension strength, leg extension strength, and gait speed. The correlation between CT-derived CSMA and DXA-derived SMM along with their association with physical function was examined. Results: After controlling for related factors, the partial correlation coefficient of muscle cross-sectional area (CSA) with physical function was larger than that of DXA-derived SMM for gait speed in men (p=0.002) and knee extension strength in women (p=0.03). The partial correlation coefficient of quadriceps (Qc) CSA with physical function was larger than that of DXA-derived SMM for leg extension power in both sexes (p=0.01), gait speed in men (p<0.001), and knee extension strength in women (p<0.001). Conclusion: Mid-thigh CT-derived CSMA, especially Qc CSA, showed significant associations with grip strength, knee extension strength, and leg extension power, which were equal to or stronger than those of DXA-derived SMM in community-dwelling middle-aged and older Japanese people. The mid-thigh CSMA may be a predictor of mobility disability, and is considered to be useful in the diagnosis of sarcopenia.

Key words: Muscle mass, CT, DXA, muscle strength, gait speed.


 

Introduction

As the population ages, healthy life expectancy has received a considerable amount of attention. Reductions in healthy life expectancy are strongly associated with aging of the musculoskeletal system (1). Muscle weakness is an important determinant of physical function in older persons (2). In 1989, Rosenberg proposed the term ‘sarcopenia’ to describe this age-related decrease in muscle mass (3). Thereafter, sarcopenia has been defined as the loss of skeletal muscle mass and strength that occurs with advancing age (4). Sarcopenia is characterized by an age-related decline in skeletal muscle mass (SMM) plus low muscle strength and/or low physical performance. In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) (5) and in 2011, the International Working Group on Sarcopenia (IWGS) (6) proposed an operational definition and diagnostic strategy for sarcopenia; therefore, it has become widely used throughout the world. In 2014, Chen et al. reported a consensus of the Asian Working Group for Sarcopenia (AWGS) (7). Furthermore, the EWGSOP recently revised the consensus for sarcopenia (8).
SMM measured by dual-energy X-ray absorptiometry (DXA) is used as the gold standard in the diagnosis of sarcopenia. In 1998, Baumgartner et al. reported a method for evaluating SMM from DXA measurements (9). Skeletal muscle mass index (SMI) was defined as appendicular muscle mass (AMM) /height squared. Whole-body DXA scans are available for dividing the body into bone, fat, and lean components (10). In the limbs, lean tissue mass is employed as a surrogate for muscle mass. However, whole-body DXA scans are not widely used.
On the other hand, computed tomography (CT) is used to assess a cross-sectional muscle area (CSMA). CT is the gold standard for estimating CSMA in research. Previously, we reported sex- and age-related differences in mid-thigh composition using CT in middle-aged and older Japanese individuals (11). (from their 40s to 80s) In that study with a large population, covering a wide range of generations, CSMA determined by mid-thigh CT decreased with age mainly in the quadriceps cross-sectional area (Qc CSA), especially in women. CT is considered to be a very precise imaging method. CSMA is separated into individual muscle sections, and adipose tissue is separated from the other soft tissues of the body by CT. CT is more sensitive to small changes in muscle mass than DXA (12). In previous studies, CSMA determined by mid-thigh CT has shown an association with muscle strength (13, 14) and gait speed (15, 16). However, these studies involved a small sample size (13) and did not cover a wide range of generations (13-16) as we did (1). Even in the Health, Aging and Body Composition study (15), with as many as 2979 participants, all participants were in their 70s. Furthermore, no studies evaluating the difference between CT-derived CSMA and DXA-derived SMM in relation to physical function have been performed. Therefore, we examined the association of muscle strength and gait speed with CSMA and evaluated the difference between CT-derived CSMA and DXA-derived SMM in relation to physical function in community-dwelling middle-aged and older Japanese individuals.

 

Methods

Subjects

The study participants were derived from the seventh wave survey (July 2010 to July 2012) of the National Institute for Longevity Sciences – Longitudinal Study of Aging (NILS-LSA). NILS-LSA is a study aiming to assess the normal aging process and identify factors of aging using medical, physiological, nutritional, and psychological examinations. Participants in the NILS-LSA included randomly selected age- and sex-stratified individuals from the residents in the NILS neighborhood areas of Obu City and Higashiura Town in Aichi Prefecture. The first wave examination of the NILS-LSA was conducted from November 1997 to April 2000 and comprised 2267 participants. This was a dynamic cohort study; thus, even when some participants were lost to follow-up, the same number of participants of the same age were newly chosen and recruited to ensure that the total number in each generation (40s, 50s, 60s and 70s) was kept constant age- and sex-matched random samples of the same number of dropouts were recruited, except for those aged >79 years. Male and female participants aged 40 years were also newly recruited every year. Details of the NILS-LSA have been previously reported.17 Of the 2330 participants in the seventh wave survey, 943 men and 875 women were included in the present study, all of whom underwent all of the following six examinations; mid-thigh CT, DXA, grip strength, knee extension strength, leg extension power, and gait speed. The study protocol was reviewed and approved by the ethics committee of the National Center for Geriatrics and Gerontology, and written informed consent was obtained from all subjects.

Mid-thigh CSMA measurement

Details of mid-thigh CSMA measurement have been previously reported (11) CSMA, involved whole-muscle CSA (defined as muscle CSA), and Qc CSA were measured. With the subject in a supine position, right mid-thigh CSA was measured by CT (X-Vision; Toshiba, Tokyo, Japan, and SOMATOM Sensation 64; Siemens, Munich, Germany) at the midpoint from the inguinal crease to the proximal pole of the patella (Fig. 1). A single-slice CT image was obtained with a minimal slice width of 10 mm for X-Vision and 5 mm for SOMATOM Sensation 64. CSA data were analyzed using Quick Grain version 5.2 software (Inotech, Hiroshima, Japan). The differences in CT voxels between air and skin, fat and muscle, and muscle and bone were checked by an orthopedic surgeon before calculation of CSMA by automatic tracing of the margins. CSA of subcutaneous fat, intermuscular fat, and bone CSA were removed when muscle CSA (cm2) was measured (Fig. 1). Qc CSA (cm2) was measured by manual tracing of the Qc margin by one research assistant who received training before starting to trace a large number of samples. Until she became accustomed to tracing, two other persons, both orthopedic surgeons, joined the discussion concerning how to determine where the margin should be placed. After starting the large number of tracings, when she faced difficult cases and felt uncertain, the margins were decided through discussions with the two surgeons.

Figure 1
Cross-sectional muscle area determined by mid-thigh computed tomography

CSMA was measured at the midpoint from the inguinal crease to the proximal pole of the patell; Cross-sectional areas of subcutaneous fat, intermuscular fat, and bone have been removed.

 

SMM measurement

SMM was measured by a QDR-4500 DXA (Hologic, Bedford, MA, USA). The subject lay in a supine position on the DXA table with limbs close to the body. The whole-body lean soft tissue mass was divided into the arms, legs, and trunk. AMM was determined by combining the lean soft tissue mass of the regions of arms and legs. SMI (kg/m2) was calculated by AMM / height squared. SMI and lean mass of right lower extremity / height squared were included in analysis.

Physical function measurement

Grip strength (kg) was measured using a T.K.K.4301 grip dynamometer (Takei, Niigata, Japan). In the standing position, with the arms straight by the sides, the subject gripped the dynamometer as hard as possible without pressing the instrument against the body or bending at the elbow. Two tests were performed for each hand, and the maximum value was included in the analysis. Knee extension strength (kg) was measured using a T.K.K.1281 (Takei). The subject was seated on a chair with his or her hip and knee joints flexed to 90° and advised to extend the knee joint. Three tests were performed for each leg; the maximum value was included in analysis. Leg extension power (watts) was measured using a T.K.K.4236 (Takei). The subject was fastened by a seat belt to the chair. In the starting position, the feet were placed on a footplate attached perpendicularly to a rail. The subject was advised to extend his or her legs as quickly and powerfully as possible, so that the footplate started sliding horizontally on the rail. The maximum value of eight tests was included in analysis. Gait speed (m/s) was measured using the YW-3, which is a walking analysis system using the sheet type sensors made by Yagami Co Ltd, (Nagoya, Aichi, Japan). The subject was asked to walk a distance of 10 m along a walkway, with approximately 1 m before and after the test distance for the acceleration and deceleration required to walk at the usual speed.

Other parameters

Body height (cm) and weight (kg) were assessed for all subjects, and body mass index (kg/m2) was calculated by weight/height squared. Medical history and smoking habits were obtained by self-administered questionnaires. Total energy intake per day (kcal/day) was assessed using three-day diet records.18 Foods were weighed separately on a scale before cooking, or portion sizes were estimated. Subjects also photographed meals before and after eating using disposable cameras. Trained dieticians calculated total energy intake per day based on the three-day dietary records. Alcohol intake (ethanol ml/day) over the previous year was assessed using a food frequenced questionnaire administered by trained dieticians during interviews with the subjects. Moreover, trained interviewers employed a questionnaire to analyze the frequency, intensity, and duration of exercise using a physical exertion manual,19 and physical activity (MET×min /year) during leisure time was calculated. One metabolic equivalent (MET) is defined as the amount of oxygen consumed while sitting at rest and is equal to 3.5 ml O2 per kg body weight.

Statistical analysis

Continuous variables were expressed as the mean ± standard deviation, and class variables were expressed as number (% of total men or women). Differences in continuous variables between men and women were tested by Student’s t-test, and the associations of class variables between men and women were tested by χ2-test.
To evaluate the association of SMI with CSMA, we examined scatter plot and regression analysis in both sexes. We examined the association of CSMA or DXA-derived SMM with physical function using Pearson’s partial correlation coefficient adjusted for age, alcohol intake, leisure time activity, total energy intake, smoking habits, medical history of stroke, hypertension, heart disease, hyperlipidemia, and diabetes (information on these were mostly collected through self-administered questionnaires mailed approximately one month in advance to each participant before their arrival at the clinic, and the answers were checked by trained interviewers). The difference in the partial correlation coefficient between CT-derived CSMA and DXA-derive SMM was examined in a manner described by Meng et al (20).
Statistical testing was carried out using the Statistical Analysis System release 9.3 (SAS Institute, Cary, NC, USA), and p<0.05 was considered to indicate a statistical significance.

 

Results

For the baseline characteristics, the proportion of men and women was similar in all age groups (Table 1). The number of subjects in the 80s group was approximately one-quarter of that in the other groups. SMI, muscle CSA, Qc CSA, grip strength, knee extension strength, leg extension power, and gait speed were significantly higher in men than in women (p<0.001). Current smoking rate and the prevalence of hypertension, heart disease, and diabetes were higher in men than in women (p<0.001, p<0.001, p=0.02, respectively).

Table 1
Characteristics of subjects by sex

The values are expressed as mean ±standard deviation and a number (% of total men or women) of samples; p-values were obtained using the t-test for continuous data and the χ²-test for categorical data; BMI, body mass index; AMM, appendicular muscle mass; SMI, skeletal muscle mass index; CSA, cross-sectional area; Qc, quadriceps

 

Figure 2 shows a positive correlation between DXA-derived SMI and CT-derived CSMA. In both sexes, SMI showed an association with muscle CSA (r=0.80, p<0.001 in men, r=0.71, p<0.001 in women) and Qc CSA (r=0.75, p<0.001 in men, r=0.63, p<0.001 in women).

Figure 2
Regression analysis showing the association between skeletal muscle mass index (SMI) and muscle cross-sectional area (muscle CSA) and quadriceps cross-sectional area (Qc CSA) in men and women

 

The association of CSMA and DXA-derived SMI with physical function is presented in Table 2. Muscle CSA showed a significant association with grip strength (r=0.33 in men, r=0.32 in women), knee extension strength (r=0.44 in men, r=0.46 in women), and leg extension power (r=0.34 in men, r=0.28 in women) in both sexes. Qc CSA showed a significant association with grip strength (r=0.34 in men, r=0.30 in women), knee extension strength (r=0.50 in men, r=0.49 in women), and leg extension power (r=0.39 in men, r=0.31 in women) in both sexes. CSMA in particular showed a strong association with knee extension strength in both sexes. Muscle CSA and Qc CSA showed a weak association with gait speed in men (r=0.10, r=0.12, respectively). SMI showed an association with grip strength (r=0.35 in men, r=0.33 in women), knee extension strength (r=0.47 in men, r=0.41 in women), and leg extension power (r=0.33 in men, r=0.24 in women) in both sexes. SMI in particular showed an association with knee extension strength in both sexes but no association with gait speed in either sex.

Table 2
The association and respective differences of CSMA or SMI with physical function

Pearson’s partial correlation coefficient was calculated controlled for age, alcohol intake, leisure time activity, total energy intake, smoking habit and medical history. The difference in the partial correlation coefficient between CSMA and SMI was examined according to Meng et al. CSMA, cross-sectional muscle area; CSA, cross-sectional area; Qc, quadriceps; SMI, skeletal muscle mass index

 

The difference in the partial correlation coefficients for CT-derived CSMA and DXA-derived SMI is also presented (Table 2). The partial correlation coefficient of muscle CSA with physical function was larger than that of DXA-derived SMI for gait speed in men (p=0.002) and knee extension strength in women (p=0.03). The partial correlation coefficient of Qc CSA with physical function was larger than that of DXA-derived SMI for leg extension power in both sexes (p=0.007), gait speed in men (p<0.001), and knee extension strength in women (p<0.001). For grip strength, almost no difference in the partial correlation coefficient was observed between CSMA and DXA-derived SMI in both sexes.
The association of CSMA or DXA-derived lean mass of right lower extremity / height squared with physical function and the difference in partial correlation coefficient between CT-derived CSMA and DXA-derived lean mass of right lower extremity / height squared are shown in Table 3. Lean mass of right lower extremity / height squared showed an association with grip strength (r=0.30 in men, r=0.30 in women), knee extension strength (r=0.46 in men, r=0.40 in women), and leg extension power (r=0.32 in men, r=0.25 in women) in both sexes. Additionally, it showed an association with knee extension strength in both sexes and a weak association with gait speed in women (r=0.08). The partial correlation coefficient of muscle CSA with physical function was larger than that of DXA-derived lean mass of right lower extremity / height squared for gait speed in men (p=0.001) and knee extension strength in women (p=0.008). The partial correlation coefficient of Qc CSA with physical function was larger than that of DXA-derived lean mass of right lower extremity / height squared for knee extension strength and leg extension power in men (p=0.04, p<0.001) and women (p<0.001, p=0.02 respectively), and gait speed in men (p<0.001), For grip strength, no difference in the partial correlation coefficient between CT-derived CSMA and DXA-derived lean mass of right lower extremity / height squared was found in either sex.

Table 3
The association and respective differnces of CSMA or lean mass of right lower extremity / height² with physical function

The difference in the partial correlation coefficient between CSMA and lean mass of right lower extremity / height² was examined according to Meng et al. CSMA, cross-sectional muscle area; CSA, cross-sectional area; Qc, quadriceps; rLM/h2, lean mass of the right lower extremity/height2

 

Discussion

The present study indicated that Qc CSA determined by mid-thigh CT showed a better association with leg extension power in both sexes, knee extension strength in women, and gait speed in men than DXA-derived SMM, whereas muscle CSA showed a better association with knee extension strength in women and gait speed in men than did DXA-derived SMM.
Previous studies have demonstrated a nice correlation between DXA-derived SMM and CT-derived CSMA for the lower limb region (21-23). Wang et al (21) reported a good (r=0.95, p<0.001) correlation between DXA-derived appendicular lean mass and multislice CT-derived muscle mass in 17 healthy men aged 35.3±12.7 years and 8 men aged 35.0±4.9 years with acquired immunodeficiency syndrome (AIDS). On the other hand, Visser et al. (22) reported a good (r=0.97, p<0.001) correlation between DXA-derived mid-thigh lean mass and single-slice mid-thigh CT-derived muscle mass in 30 healthy men aged 73.9±2.2 years and 30 healthy women aged 73.6±2.3 years. Levin et al. (23) also reported a good (r=0.86, p<0.001) correlation between DXA-derived thigh lean mass and single-slice mid-thigh CT-derived muscle mass in 18 healthy men and 25 healthy women aged 39±13 years. Our study had a larger sample size and wider age range, including middle-aged and older subjects, and showed a similar correlation between DXA-derived SMI and CT-derive CSMA.
CSMA determined by mid-thigh CT has been shown to have an association with muscle strength (13, 14). In the present study, CSMA showed an association with muscle strength and power in both sexes, especially with knee extension strength. Thus, our results confirm those of the previous studies. Less muscle mass (smaller CSMA) is associated with increased risk of mobility loss in older men and women (2). CT-derived CSMA may be a predictor of mobility disability.
In the present study, the association between Qc CSA and leg extension power by mid-thigh CT was examined. Qc CSA showed a significant association with leg extension power, and the partial correlation coefficient of Qc CSA with physical function was larger than that of DXA-derived SMM for leg extension power in both sexes. The correlation coefficients detected for grip strength were comparatively lower than those for knee extension strength for both CSA and SMI. This may be due to the «regional sarcopenia» phenomenon because sarcopenia may affect only a limited number of muscle groups in the earlier stages. Low Qc muscle mass is associated with postural instability (24). Therefore, low muscle mass of the lower extremities is particularly important, as it may lead to various physical dysfunctions (25). Mid-thigh CT separates CSMA into Qc CSA and non-Qc CSA and is a useful method for evaluating the association between Qc CSA and physical function.
Previous studies have evaluated the association of CT-derived CSMA or DXA-derived SMM with physical function. However, the intensity of the association between CT-derived CSMA and DXA-derived SMM on physical function has not been compared. In the present study, CT-derived CSMA showed an association with muscle strength and power that was equal to or stronger than that of DXA-derived SMM. The statistical significance of our results, however, may have little relevance in clinical practice because the correlation coefficients found here were rather low (most of them were far below 0.50, e.g., that between CSMA and gait speed in males was 0.10.
To examine whether there are any differences, the analyses were performed separately in the two age groups, either younger or older than 60 years old. However, the results were not different between the younger group and the older group.
We reported that the pattern of age-related decrease in DXA-derived SMI is different between men and women, although SMI did not differ according to age in women (26). DXA-derived SMM is thought to underestimate the fat component (27), and DXA-derived SMM might involve a fat component.
This study had several limitations. First, a selection bias imposed by the longitudinal design might exist in this study. NILS-LSA is a longitudinal study; therefore, the seventh wave survey participants tended to be healthier than those who dropped out of the study. Second, CT-derived CSMA was a cross-sectional area only at mid-thigh. CT-derived CSMA may not completely reflect the skeletal muscle mass in the entire body. Furthermore, concerns about radiation exposure limit the use of these whole-body imaging methods for routine measurement. With regard to the covariant adjustment for the Pearson partial correlation coefficient, we tried to adjust for body weight, but we found that the correlation coefficient became substantially lower for both CSA and SMI, although the results of the comparison analyses between CSA and SMI were the same, namely that CSA was greater than or equal to SMI. Another covariant we should discuss that we did not consider was the possible toxic effects of some drugs that some participants may have been taking.
Adipose tissue is distinguished from other soft tissues of the body, including intramuscular lipid content, by CT.5 The increasing fat infiltration into muscle with aging may be a factor for prognosis for future mobility limitations independent of muscle strength. In the present study, we could not consider the possible presence of adipose tissue infiltrates in muscles. This phenomenon may be especially relevant in sarcopenic obesity. The methodology we utilized here was unable to measure this phenomenon. Therefore, in the near future, we will conduct new analyses utilizing additional imaging software, considering the CT attenuation value. However, at present, we are not sure if the DXA measurement would be more accurate in distinguishing lean from fat tissue because DXA-measured SMI has been reported to not change according to aging in women, whose muscle should contain more lipids as they age.
Evaluation of intramuscular lipid content is important for an assessment of muscle quality. We are now examining intramuscular fat evaluation using mid-thigh CT, and we will report muscle quality assessed by mid-thigh CT examination in the future.
Another issue we have to consider with regard to the application of this new muscle mass measuring method in clinical practice is that CT, despite being an excellent tool for measuring muscle mass, costs comparatively more and results in some radiation exposure, although using only one slice as in our method results in low exposure levels. If the muscle cross-sectional area can also be measured by ultrasound, that would be a low-cost and comparatively safe examination that does not expose the patient to radiation.
In conclusion, the present study indicated that mid-thigh CT-derived CSMA, especially Qc CSA, showed significant associations with grip strength, knee extension strength and leg extension power, which were equal to or stronger than those of DXA-derived SMM in community-dwelling, middle-aged and older Japanese people.

 

Funding: The present study was supported in part by grants from The Research Fund for Longevity Sciences (25-28, 25-22) from the National Center for Geriatrics and Gerontology (NCGG), Japan.
Acknowledgements: The authors thank the participants and their colleagues involved in the NILS-LSA.
Conflict of interest: There are no declared conflict of interest.

 

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MULTI-COMPONENT EXERCISE WITH HIGH-INTENSITY, FREE-WEIGHT, FUNCTIONAL RESISTANCE TRAINING IN PRE-FRAIL FEMALES: A QUASI-EXPERIMENTAL, PILOT STUDY

 

N.W. Bray1, G.J. Jones1, K.L. Rush2, C.A. Jones3, J.M. Jakobi1

 

1. School of Health and Exercise Sciences, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada; 2. School of Nursing, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada; 3. Southern Medical Program, Faculty of Medicine, University of British Columbia Okanagan, Kelowna, British Columbia, Canada.
Corresponding author: Jennifer M. Jakobi, School of Health and Exercise Sciences, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, British Columbia, Canada, V1V 1V7, jennifer.jakobi@ubc.ca

J Frailty Aging 2020;9(2)111-117
Published online March 16, 2020, http://dx.doi.org/10.14283/jfa.2020.13

 


Abstract

Background: No study has performed an exercise intervention that included high-intensity, free-weight, functional resistance training, and assessed frailty status as an inclusion criteria and outcome measure via original, standardized tools, in pre-frail females. Objectives: Determine if the intervention strategy is not only feasible and safe, but can also improve frailty status, functional task performance, and muscle strength. Design: Pilot, quasi-experimental. Setting: Community. Participants: 20 older-adults with pre-frailty characteristics. Intervention: 12-weeks (3 days/week, 45-60 minutes/session) of multi-component exercise, inclusive of aerobic, resistance, balance and flexibility exercises. The crux of the program was balance and resistance exercises, the latter utilized high-intensity, free-weight, functional resistance training. The control group maintained their usual care. Measurements: 1) Feasibility and safety (dropout, adherence, and adverse event); 2) Frailty (Frailty Phenotype, Clinical Frailty Scale, and gait speed); 3) Functional task performance (grip strength and sit-to-stand time); and 4) Isometric and isotonic strength of the knee extensors and elbow flexors. Results: No participants dropped out of the intervention or experienced an adverse event, and adherence averaged 88.3%. The exercise group became less frail, whereas the control group became more frail. There was a significant within-group improvement in exercise participants gait speed (p ≤ 0.01, +0.24 m/sec), grip strength (p ≤ 0.01, +3.9 kg), and sit-to-stand time (p ≤ 0.01, -5.0 sec). There was a significant within-group improvement in exercise participants knee extension isometric torque (p ≤ 0.05, +7.4 Nm) and isotonic velocity (p = ≤ 0.01, +37.5 ˚/sec). Elbow flexion isotonic velocity significantly declined within the control group (p ≤ 0.01, -20.2 ˚/sec) and demonstrated a significant between-group difference (p ≤ 0.05, 40.73 ˚/sec) post-intervention. Conclusions: The intervention strategy appears to be feasible and safe, and may also improve frailty status, functional task performance, and muscle strength. These results help calculate effect size for a future randomized controlled trial.

Key words: Older age, resistance training, muscle strength, quality of life, females.


 

Introduction

Exercise is considered a suitable therapy to reverse frailty (1–3) but it is difficult to determine which characteristics of an exercise program are most effective (4, 5). Most exercise intervention studies do not adequately assess the level of frailty (4), convoluting the understanding of positive adaptation and limiting the potential to apply spectrum specific exercise recommendations suggested in a recent literature review (1).
Frailty is also a dynamic process where transitions are subtle (6, 7), bidirectional (8), and sex-dependent; females experience frailty differently than males, succumbing to the syndrome earlier yet living longer (9,10). Older females also represent a larger percentage of the aging demographic (11), and pre-frail females outnumber those that are frail (12, 13). Thus, there is considerable need to identify exercise interventions that would improve frailty status in this large and growing cohort;
A scoping review identified only 15 exercise studies that used a frailty identification tool to classify participants’ frailty status at the onset and conclusion of an intervention (14). However, only five studies (15–19) included a clearly defined pre-frail sample population and only one focused exclusively on females, which were identified via a modified frailty assessment tool (17). These studies generally utilized higher-repetition, low-intensity, single-joint resistance training exercises. To-date, no study has utilized validated frailty identification tools as both an inclusion criteria and outcome measure to assess an exercise intervention that incorporates high-intensity, free-weight, functional resistance training, exclusively in pre-frail females. Despite a lack of evidence supporting such claim, this may be due to the commonly held belief that such resistance training exercises are unsafe (20).
We performed a pilot study to determine if a multi-component exercise (MCE) program, inclusive of high intensity, free-weight, functional resistance training, is not only feasible and safe, but can improve frailty status, functional task performance, and measures of strength in pre-frail females. It was hypothesized that the exercise group (EX) would improve frailty status, functional task performance, and muscle strength, in comparison to a control group (CON).

 

Methods

Experimental Overview

EX participants completed a 12-week exercise intervention (3-days/week, 45-60 min/session). The CON maintained their normal routine for the same duration. Participants of both groups were assessed for frailty status, functional task performance, and muscle strength at week 0 (pre-intervention) and 13 (post-intervention), and the latter two measures were repeated at weeks 5 and 9 for the EX (Figure 1).

Figure 1
Overview of the multi-component exercise (MCE) intervention and assessments. Similar to resistance training, participants began balance training at different levels and progressed based upon individual ability. The balance training was progressed when the upper limit for time or repetition range was achieved without loss of balance. Training sessions concluded with a flexibility training, utilizing just a kneeling hip flexor flexibility exercise (30). Participants started by stretching for 15 seconds (sec) per leg, and added 15 sec each week, up to a maximum of 60 sec, for a total time of 2 min

 

Subjects

Participants were recruited from the community. Inclusion criteria consisted of: 1) Females ≥ 65 years of age; 2) A Montreal Cognitive Assessment (21) score ≥ adjusted normative values (22); 3) No contraindications to exercise, as determined by the Physical Activity Readiness–Questionnaire Plus; 4) No major injuries/surgeries to the dominant arm or leg in the last six months; 5) Fluent in English; and 6) A pre-frail frailty status.
Initial recruitment found 53 older adults interested but only 21 agreed to complete the pre-intervention assessment, with one being excluded. As a quasi-experimental study, participants were randomized to the EX and CON based upon their perceived availability to participate in exercise. Current interventions utilizing exercise require 80% adherence (23). As a result, 9/20 participants were placed in the EX.
All participants read and signed a letter of informed consent. Ethical approval was granted by the institutional Research Ethics Board (H16-00712). All experimental procedures involved in the study conformed to the declaration of Helsinki.

Multi-Component Exercise (MCE)

Kinesiology students led each session. Details of the aerobic warm-up, as well as the balance exercises and flexibility cool-down are within Figure 1. Resistance training was divided into three blocks of four weeks; each new block decreased the number of repetitions to be completed and subsequently increased the resistance, thus, transitioning from training muscular endurance to strength. Within each block, the resistance was also increased when participants reached the upper limit of the repetition range for all sets. Rest periods between sets ranged from 1-3 minutes. To aid progressive overload, participants disclosed their rating of perceived exertion after the last set of every exercise. Details about the training principles can be found in our companion article, “Practical Implications for Strength and Conditioning of Older Pre-Frail Females” (24).
Four free-weight resistance exercises were selected: 1) Squat; 2) Deadlift; 3) Bench Press; and 4) Leg Press. Exercises 1-3 replicate functional movements, such as standing from a toilet, opening a door, and picking up groceries from the ground; these exercises utilized dumbbells (Hex Dumbbell, Northern Lights Inc, Cornwall, ON) and/or barbells (The Bella 2.0 – Females’s Bar, Rogue Fitness; Columbus, OH) with weighted plates (Virgin Rubber Grip Olympic Plates, Element Fitness; Latvia). The fourth exercise supplemented the Squat exercise but was less technically demanding, and utilized an incline leg press machine (TuffStuff PPL-960 45°Leg Press, TuffStuff Fitness Equipment, Chino, CA). Each session started with the squat or bench press and finished with the deadlift or inclined leg press.

Experimental Assessments

Feasibility and Safety: Participant dropout and adverse events were recorded in an ongoing electrical document log. Adherence rates were maintained in an ongoing paper log that participants were required to sign upon arrival to each intervention session.
Frailty Status: Participants were included in this study if they were classified as pre-frail according to guidelines in at least one of the following three tools:
1) 1-2 on the frailty phenotype (FP) (25)
2) 4-6 on the clinical frailty scale (CFS) (26)
3) Gait speed (GS) of ≥ 1.0 – < 1.5 m/sec indicated pre-frailty (27)

Previous research suggests that several frailty tools may provide a more reliable measure of frailty status, and that the FP and CFS do not always provide the same classification (9,28). Therefore, GS was used as a third frailty criterion.
Functional Task Performance: GS was assessed across 8 meters (m), excluding acceleration (2m) and deceleration (2m) zones, at a self-selected walking speed that was considered normal. The GS test was completed twice and the fastest trial was used for data analysis. Handgrip strength was measured while standing with a dynamometer (Baseline Smedley, Fabrication Enterprises Incorporated, White Plains, NY) held at arm’s length and slightly abducted. The dynamometer was squeezed as hard as possible for three seconds, and completed twice for each hand. The order of grip testing was randomized and trials occurred between gait tests. The highest score was used for both functional task performance and FP. The sit-to-stand (STS) task was adopted from the short physical performance battery (29).
Muscle Strength Performance: The Biodex Dynamometer System 4 Pro (Biodex Medical Systems Incorporated, Shirley, NY) was used to assess peak torque/velocity of isometric/isotonic knee extension (KE) and elbow flexion (EF). For KE and EF, participants were seated with their hips flexed to ~100º. Restraining straps crossed the chest and opposite hip, and for KE, a third was secured across the thigh of the tested leg. For KE, the lateral femoral condyle of the dominant leg was aligned with the dynamometer center of rotation. To account for the effect of gravity, the weight of the limb was calculated by the Biodex with the knee extended to 160º. For EF, the medial epicondyle of the elbow was aligned with the dynamometer center of rotation. The shoulder was slightly forward flexed (10-15º) and abducted. Positioning was measured, recorded, and replicated for all sessions.
Isometric KE and EF contractions were executed at a joint angle of 90º. Isotonic KE was also initiated from 90º but EF isotonic contractions were initiated from 160º. Range of motion of isotonic contractions was 90-160º for KE and the inverse for EF. Isotonic resistance was 20% of the peak torque from the strongest isometric contraction of the pre-intervention assessment. Participants completed five isometric and isotonic contractions for both KE and EF, with two minutes of rest between contractions. All contractions were recorded and the highest value was used for data analysis. The analogue signal was sampled at 2,000 Hz and stored for offline analysis using the Biodex software.

Statistical Analysis

Pre-intervention characteristics were compared using an independent sample t-test. A sample size calculation for a 2-tailed study design advised a minimum sample size of six subjects per group to attain a statistical power of 0.80 for the KE strength variable. A two-way mixed ANOVA of time by group assessed all outcomes. A one-way ANOVA was used to evaluate any significant interactions and main effects. The EX was also examined over time using a one-way repeated measures ANOVA, with a Bonferroni post-hoc test. Sphericity was assessed (Mauchly’s) and a Greenhouse-Geisser correction applied if violated (p < 0.05). Data that violated normality and homogeneity of variances was transformed using the function Log10. Statistical significance was p ≤ 0.05. All values are reported as mean ± standard deviation (SPSS Statistics V.24, IBM Canada Ltd. Markham, Ontario).

 

Results

Characteristics: Participant characteristics were similar between groups (Table 1). Three CON participants were removed from the analysis because they were unable to complete the post-intervention assessment at the required date due to a fall-related injury unrelated to the study (n = 2) or illness (n = 1). No EX participants dropped out or experienced an adverse event during the intervention, and intervention adherence averaged 88.3%. One EX participant completed <65% of exercise sessions (seasonal flu) and was subsequently removed from the final analysis. A shoulder injury, unrelated to the exercise program, precluded one EX participant from completing the grip strength, STS, and EF measures at week 13.

Table 1
Participant characteristics (mean ± SD)

SD = standard deviation; CON = control; EX = exercise; BMI = body mass index; MoCA = Montreal Cognitive Assessment; cm = centimeters; kg = kilograms; kg/m2 = kilograms per meter squared.

 

Frailty: There was a time main effect for the FP (F (1,14) = 8.5, p ≤ 0.01, partial η2 = 0.4) and CFS (F (1,14) = 4.8, p ≤ 0.05, partial η2 = 0.3) but no group main effect (F (1, 14) = 1.423, p = 0.25, partial η2 = 0.09). Following the 12-week intervention, five and six participants of the EX were less frail according to the FP and CFS, respectively. Gait speed was faster for all EX participants. The CON became more frail according to the FP (n=1), CFS (n=2), and GS (n=8), respectively (Figure 2).

Figure 2
Changes in frailty status across all three frailty identification tools: A) Frailty Phenotype (FP), n = 16, B) Clinical Frailty Scale (CFS), n = 16 and C) gait speed (GS), n = 16. Pre-frailty thresholds indicated by the vertical broken lines; 1-2 on the FP, or 4-6 on the CFS, or a GS between ≥ 1.0 to < 1.5 meters per second (m/sec). The order of participants is consistent between each figure, in order to identify individual frailty scores across tools, as well as the change between time points. The arrow head indicates the direction and magnitude of change (right = negative or more frail; left = positive or less frail) from pre to post-intervention. Pre-intervention, nine, three, and thirteen participants were classified as pre-frail according to the FP, CFS, and GS, respectively. Pre-intervention, one participant was considered pre-frail according to all three tools, while seven participants were classified as pre-frail according to two tools. = exercise (EX),= control (CON) group.

 

Functional Task Performance: EX demonstrated improvements in post-intervention GS (F (1, 7) = 15.2, p ≤ 0.01, partial η2 = 0.7) and grip strength (F (1, 6) = 17.3, p ≤ 0.01, partial η2 = 0.7; Figure 3). STS time (F (1, 13) = 4.8, p ≤ 0.05, partial η2 = 0.3) in the CON was faster pre-intervention (F (1, 13) = 6.6, p = 0.02, partial η2 = 0.3) but no significant difference existed post-intervention (F (1, 13) = 0.7, p = 0.4, partial η2 = 0.0) as a result of a significant improvement in the EX (5.0 sec, F (1, 6) = 18.2, p ≤ 0.01, partial η2 = 0.8).

Figure 3
Control (CON) and Exercise (EX) group results for functional task measures

Gait speed, n = 16, grip strength, n = 15, and sit-to-stand time, n = 15 pre and post-intervention. Intra-group assessments performed only on the EX at 5 and 9-weeks. *, significant difference within the EX over time; †, significant difference between groups; ‡, significant difference within the CON over time. m/sec = meters per second; kg = kilograms; sec = seconds; wk = week

 

Muscle Strength Performance: KE isometric torque (F (1, 7) = 5.9, p ≤ 0.05, partial η2 = 0.5) and isotonic velocity (F (1, 7) = 17.5, p = ≤ 0.01, partial η2 = 0.7) improved in the EX post-intervention (Figure 4). There was a significant interaction for EF isotonic velocity (F (1, 13) = 14.8, p ≤ 0.01, partial η2 = 0.5) as the CON was slower post-intervention (-20.2 ˚/sec, F (1, 7) = 21.7, p ≤ 0.01, partial η2 = 0.8).

Figure 4
Control (CON) and Exercise (EX) group results for strength measures

Knee extension (KE) isometric torque (A1), n = 16, KE isotonic velocity (A2), n = 16, Elbow flexion (EF) isometric torque (B1), n = 15 and EF isotonic velocity (B2), n = 15 pre and post-intervention. *, significant difference within the EX over time; †, significant difference between groups; ‡, significant difference within the CON over time. Pre = pre-intervention; post = post-intervention; Nm = newton meters; ˚/sec = degrees per second

 

Discussion

Findings suggest that this intervention strategy appears to not only be feasible and safe for pre-frail females, but it can also improve frailty status, functional task performance, and strength measures. Conversely, CON participants became more frail over the same time period, showed little change in GS, grip and KE strength, and suffered a significant decline in EF isotonic strength.
This is the first study to include high-intensity, free-weight, functional resistance training in pre-frail older females, assessed via non-modified frailty tools pre and post-intervention. The lack of adverse events suggest that this style of training is safe when supervised and programmed correctly. The high adherence rates and lack of dropout may indicate a high degree of enjoyment. Previous interventions in pre-frail older adults have generally utilized high-repetition, low-intensity, single-joint resistance training exercises, which, despite a lack of evidence, may be attributed to the commonly held belief that the alternative is unsafe (20).
Although frailty status was inconsistent between tools, we believe that by utilizing a combination of tools, the sample is reflective of the pre-frail/vulnerable population under investigation. For example, at baseline, our participant with the fastest gait speed was also considered pre-frail according to the FP. Frailty is a dynamic syndrome, as indicated by the different levels of frailty described across most assessment tools (25,26), and there is growing support for disassociating frail from pre-frail (1,5). Sex-differences also further complicate frailty (9,10). Previous research have reported a wide-range of values for the percentage (21-48%) of participants that have demonstrated an improvement in frailty status. Regardless of the tool, our percentage (> 63%) of participants that reversed frailty exceeds all other previous interventions that have included a pre-frail population, and measured frailty status pre and post-exercise intervention (15–19).
All measures of functional task performance consistently improved for the EX. Kwon and colleges (17) assessed both GS and grip strength, but only reported improvements in the latter (2.3 kg) for their intervention group, which was less than the 3.9 kg change observed in our EX. Improvements in functional task performance complement the observed changes in the Biodex measures.
The EX demonstrated significant improvement in KE isometric and isotonic strength post-intervention. Additionally, our EX maintained EF isotonic strength while the CON experienced a significant decline. Both Chan et al., (16) and Ng et al., (19) reported improvements in KE isometric strength in both their exercise and non-exercise groups post-intervention, and therefore, exercise may not be responsible for improvement. Our study is the first to identify strength values for isotonic KE, as well as isometric and isotonic EF in pre-frail older females, as part of an exercise intervention that used standard frailty assessment tools as both an inclusion criteria and outcome measure.
Synergistically (24), our study findings suggest that this intense resistance training program is not only safe for pre-frail females, but necessary to make enhanced improvements in frailty status, functional task performance, and muscle strength. However, this study is not without limitation. The sample size was relatively small but strength measures were appropriately powered to observe statistically meaningful changes. Moreover, the small group size likely positively influenced participants’ adherence to the program (88.3%). Further work is needed to assess the factors that contribute to adherence in this population. Given the limited number of study personnel, the lead student investigator conducted the exercise training and was not blinded to group assignment but pre-intervention scores were unavailable at intra and post-intervention testing, and file names were coded during analysis. Despite the limitations, we believe the findings support undertaking a large randomized controlled trial.

 

Conclusion

MCE inclusive of high-intensity, free-weight, functional resistance training is feasible and safe in pre-frail older females. When compared to previous studies that have measured pre-frailty status as both an inclusion criteria and outcome measure, it appears to lead to greater improvements in frailty status, functional task performance, and muscle strength. A larger randomized controlled trial is required to confirm our findings.

 

Funding: Partial funding for this study through the Canadian Institutes for Health Research (CIHR) Grant # 385692. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgments: We wish to acknowledge the support from; Flaman Fitness™ and the Okanagan Men’s Shed Club for generously donating the exercise equipment, graduate students (Rowan Smart and Sam Kuzyk) and senior undergraduate students (Anup Dhaliwal, Brett Yungen, Savannah Frederick, Paul Cotton and Cydney Richardson), and all the participants involved in this study.
Ethics approval and consent: All participants read and signed a letter of informed consent. Ethical approval was granted by the institutional Research Ethics Board (H16-00712).
Availability of the data and materials: The original data and materials are available through the institutions open access graduate thesis repository https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0353165
Competing interests: None
Trial Registration: This study was prospectively registered with ClincalTrials.gov (NCT02952443) on October 31, 2016.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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28. Lytwyn J, Stammers AN, Kehler DS, et al. The impact of frailty on functional survival in patients 1 year after cardiac surgery. J Thorac Cardiovasc Surg 2017;154(6):1990–9.
29. Guralnik JM, Simonsick EM, Ferrucci L, et al. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 1994;49(2):M85-94.
30. Watt JR, Jackson K, Franz JR, et al. Effect of a supervised hip flexor stretching program on gait in elderly individuals. PM R 2011;3(4):324–9.

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MUSCLE STRENGTH AS A PREDICTOR OF GAIT VARIABILITY AFTER TWO YEARS IN COMMUNITY-LIVING OLDER ADULTS

 

B. Bogen1, R. Moe-Nilssen1, M.K. Aaslund1, A.H. Ranhoff2

 

1. Institute of Health and Function, Western Norway University of Applied Science., Norway; 2. Department of Clinical Science, University of Bergen, Norway.
Corresponding author: Bård Bogen, Institute of Health and Function, Western Norway University of Applied Science., Norway, Email: beb@hvl.no,telephone: +47 91157142

J Frailty Aging 2019;in press
Published online July 11, 2019, http://dx.doi.org/10.14283/jfa.2019.24

 


Abstract

Background: Stride-to-stride fluctuations, or gait variability, can be captured easily using body worn inertial sensors. Previously, sensor-measured gait variability has been found to be associated with fall risk and central nervous changes. However, further research is needed to clarify the clinical relevance of this method. Objectives: In this study, we look at how gait variability is associated with muscle strength, measured two years earlier. Design, setting and participants: This is study of longitudinal associations. Participants were community-dwelling volunteers between 70-81 years. Measurements: Participants were tested while walking with a single sensor at their lower back, and they walked back and forth over a distance of 6.5 meters under four conditions: at preferred speed, at fast speed, with an added cognitive task, and while walking across an uneven surface. Gait variability in the anteroposterior (AP), mediolateral (ML) and vertical (V) directions was identified. A muscle strength score was composed by transforming hand grip strength, isometric knee extension strength and the 30 second chair rise-test to z-scores and adding them. Results: 56 individuals were analysed (mean age at baseline 75.8 (SD 3.43), 60 percent women). In a backwards regression method using age, gender and baseline walking speed as covariates, muscle strength predicted gait variability after two years for AP variability during preferred speed (Beta= .314, p=.025) and uneven surface walking (Beta=.326, p=.018). Further, muscle strength was associated with ML variability during preferred speed (Beta=.364, p=.048) and fast speed (Beta=.419, p=.042), and V variability during preferred speed (Beta=.402, p=.002), fast speed (Beta=.394, p=.004) and uneven surface walking (Beta=.369, p=.004). Conclusions: Sensor-measured gait variability tended to be associated with muscle strength measured two years earlier. This finding could emphasize the relevance of this relatively novel measure of gait in older adults for both research and clinical practice.

Key words: Gait variability, muscle strength, typical aging.


 

Introduction

Mobility limitations are common among older adults and may include reduced walking distance and walking speed (1, 2). With increasing age, walking also tends to become more unsteady (3). This can be measured as spatiotemporal fluctuations between strides, or gait variability. Gait variability can be measured using electronic walkways (footfall analysis) or body-worn inertial sensors. Using body-worn inertial sensors may be preferable because of the continuous nature of the movement signal, as opposed to foot fall analysis, where information about the gait cycle is known only from the period when the foot is in contact with the ground (4). Gait variability is considered an indication of balance control during walking (5) and may be a more sensitive measure of walking performance than for example walking speed (6). Gait variability has been found to be associated with fall risk (7) and cognitive impairment (8).
Mobility limitations have multiple and interacting causes, but weak muscles are likely to play an important role: When lacking sufficient strength, even daily life tasks can become difficult, and disability has been found to increase with decreasing muscle strength (9). Lower-extremity muscle strength has been found to be independently associated with reduced mobility in several previous studies. Knee extension strength decline has been found to explain severe walking limitations in older women with high levels of interleukin-6 (9), leg strength has been found to be associated with self-reported mobility function (10), and leg extension power has been found to be associated with walking speed (11). However, we have not found any studies investigating whether muscle strength is also associated with sensor-measured gait variability. Knowledge about this association would be helpful for providing appropriate treatment or therapy, for example strengthening exercises.
The aim of this paper is therefore to investigate whether muscle strength is associated with sensor-measured gait variability. Further, we want to investigate this association longitudinally to see whether it is possible to predict poor walking performance over time using strength measurement. Knowledge about such longitudinal associations may have relevance for clinical practice.

 

Method

Design and setting

This is an observational study with a two-year follow-up. Tests were performed in a university movement laboratory by a physiotherapist with experience with gait testing using body-worn inertial sensors.

Participants

Participants were volunteers, whose names and addresses were selected at random from the electoral roll. The sample was specified to consist of 70 percent women, living in the community and aged between 70-81 years. To be included, participants had to be able to walk unassisted for at least 10 meters and be able to give written consent.  400 names and addresses were provided for invitation to participate in the study. The Regional Ethics Committee approved the study protocol (No. 2010/1621), and all participants gave their informed, written consent.

Procedures

The participants walked a distance of 10.5 meters, where the middle 6.5 meters were captured. Gait kinematics were captured using a single body-worn inertial sensor (MTx, Xsens Technologies B.V. Enschede) worn at the lower back, attached with an elastic belt. The sensor captured accelerations in three directions: Anteroposteriorly (AP), mediolaterally (ML) and vertically (V).  The signals were transmitted to a laptop using Bluetooth technology. Gait variability was then calculated as the variation from gait cycle to gait cycle using an autocorrelation procedure (Figure 1). The metric for variability in this study are autocorrelation coefficients, and a coefficient tending towards 1.0 indicate low variability while coefficients tending towards 0.0 indicate high variability (please see Moe-Nilssen and Helbostad (12) for a detailed report of the procedure). For extra challenge, the participants walked under four conditions: At preferred speed, at fast speed, while counting backwards from 50 with intervals of three (dual-task walking) and across a rubber mat with unevenly spaced convex protrusions, covered by another, thinner mat to hide the protrusions (uneven surface walking). The participants walked back and forth during each condition and the average of both walks was used for analysis.
Strength was measured during three tasks that are in widespread use and that are assumed to represent different aspects of strength: Upper and lower extremity strength, and isometric and dynamic strength. Handgrip strength was tested using a digital myometer (MIE Medical Research Ltd, Leeds, United Kingdom). Participants sat while performing the test, resting their arm at the armrest of the chair. They were asked to squeeze the myometer as hard as they could three times for both hands. The average of all six tries was used for analyses. Isometric knee extension strength was measured in a sitting position with 90 degrees of flexion in the knee. An unelastic cord attached to a strength gauge was fitted over their ankles. The participants were asked to extend their knees with as much force as they could, three times for each leg. Isometric strength was then registered digitally (MIE Medical Research Ltd, Leeds, United Kingdom). The average of all six tries was used in analyses. The distance from the condyle of the femur to the cord around the ankle was measured for estimation of torque (Nm) (force (N)*leg length). The 30 second chair rise test required the participants to rise and sit down again on a chair as many times as they could in 30 seconds. The number of repetitions is used as output (13).
We normalized the three strength scores to z-scores (z = x – (population mean/population standard deviation)) and then added them, creating a new strength composite variable. The approach of adding z-scores to make a single composite score has not been used extensively, but may have its merit to represent a broader construct (14). Summary scores have also been used to present multiple variables with a single number in studies of physical functioning in older adults (15).
In addition to measuring strength and gait variability, participants reported which chronic diseases they had and which medication types they were taking regularly.

Analysis

The average number of chronic diseases and regular medications are reported as means, standard deviations and range (table 1). The average hand grip strength, isometric knee extension strength, 30 second chair rise-test performance and strength composite at baseline are reported as means and standard deviations for the whole group, as well as for women and men respectively, as strength is well known to differ between sexes (table 2 ). Gait variability after two years is reported as means and standard deviations (table 3). Differences between the different directions (AP, ML and V) were analyzed using repeated measures ANOVA with Bonferroni corrections (figure 2). Associations between baseline muscle strength and gait variability after two-years was done with multiple regression, using a backwards method. With two-year gait variability as the dependent variable, muscle strength, age, gender and baseline gait speed was entered as independent variables, with only variables with a p-value ≤ 0.10 remaining in the final model. Gender was included as a covariate because muscle strength is well-known to vary between men and women. Baseline gait speed was included because of potential association with gait variability. Age was included as a covariate because physical function is assumed to decrease with increasing age. Muscle strength was the predictor of interest, while age, gender and walking speed were included as potential confounders (table 3). Significance level was set at p < 0.05.

 

Results

Of the 400 invited participants, 85 accepted the invitation. Of these, 58 persons returned to the two-year follow up (reasons for not returning include death, inability to attend and not being reached). The participants who attended the two-year follow-up were not significantly different from those who did not attend with regards to age (75.8 vs 75.0, p=.259), isometric knee extension strength (93.1 Nm vs 85.5 Nm, p=.396) or preferred walking speed (1.15 m/s vs 1.10 m/s, p=.297).  Of the 58 that returned, two persons had data that could not be used due to technical error. Therefore, analyses were done for 56 participants (mean age at baseline 75.8 years (SD 3.43), 61 percent women). On average, the participants had 1.58 (SD 0.9) chronic diseases (cardiovascular disease and osteoarthritis were the most common) and took 2.11 (SD 1.79) medications regularly (medications for hypertension and hyperlipoidemia were the most common) (table 1). 11 percent of the participants reported that they did not have any chronic diseases, and 14 percent that they took no regular medications.

Table 1 Chronic diseases, regular medication use and muscle strength at baseline (n=56, mean age 75.8 (SD 3.43), 61 percent women)

Table 1
Chronic diseases, regular medication use and muscle strength at baseline (n=56, mean age 75.8 (SD 3.43), 61 percent women)

*Differences in strength between men and women were analyzed using independent samples t-tests.

 

 

The whole group had mean grip strength of 23.49 kgs (SD 9.04), mean isometric knee extension strength of 89.44 Nm (SD 46.73), mean number of repetitions on the 30 second chair rise-test of 12.57 (SD 4.14) and a strength composite score of 0.00 (SD 0.85). The men were significantly stronger than the women for all the tests (table 2).

Table 2 Descriptive data for gait speed and gait variability in the AP, ML and V directions, under all walking conditions, at two years

Table 2
Descriptive data for gait speed and gait variability in the AP, ML and V directions, under all walking conditions, at two years

 

At the two-year follow-up, the participants walked with a preferred gait speed of 1.13 m/s. During fast speed walking, they had a speed of 1.4 m/s, during dual task-walking, they had a speed of 0.83 m/s and during uneven surface walking they had a speed of 0.95 m/s. Gait variability was lowest during dual task-walking (AP autocorrelation 0.64, ML autocorrelation 0.41 and V autocorrelation 0.52). It was highest during fast speed walking (AP autocorrelation 0.78, ML autocorrelation 0.61 and V autocorrelation 0.79) (table 3). During preferred speed walking, ML variability was significantly higher than AP variability (mean difference -.185, p≤.001) and V variability (mean difference -.179, p≤.001). During fast speed walking, ML variability was significantly higher than AP variability (mean difference -.167, p≤.001) and V variability (mean difference -.178, p≤.001). During dual task and uneven surface walking, variability in all directions were significantly different from one another.

Table 3 Prediction of two-year gait variability by baseline strength composite. Final multiple regression models after backwards elimination with gender, age and preferred walking speed at baseline as covariates

Table 3
Prediction of two-year gait variability by baseline strength composite. Final multiple regression models after backwards elimination with gender, age and preferred walking speed at baseline as covariates

AP=anterioposterior. ML=mediolateral. V=vertical. WS=walking speed. DT=dual task. US=uneven surface. Baseline strength composite is the predictor variable of interest and is put in bold while covariates are included to assess confounding and are put in italics. *Independent variables predicting 2-year gait variability with p≤.10 were retained in the final model

 

Strength composite score at baseline significantly predicted high gait variability after two years in the AP (Beta .314, p=0.25), ML (Beta .364, p=.048) and V (Beta .402, p=.002) directions during preferred walking speed, and in the ML (Beta .419, p=.042) and V (Beta .394, p=.004) directions during fast speed walking. AP variability reached near significance (p = 0.075). Baseline strength composite score also predicted AP (Beta .326, p=.018) and V (Beta .369, p=.004) variability after two years during uneven surface walking, but not in any direction during dual task-walking (table 3).

 

Figure 1 The figure is an example of accelerations in the vertical (V) direction during preferred speed walking from one of the participants. The cycles resemble one another, but there is also apparent variation between the cycles

Figure 1
The figure is an example of accelerations in the vertical (V) direction during preferred speed walking from one of the participants. The cycles resemble one another, but there is also apparent variation between the cycles

Figure 2 Gait variability in the AP, ML and V directions, during all conditions. Differences in variability were analysed using repeated measures ANOVA with Bonferroni corrections

Figure 2
Gait variability in the AP, ML and V directions, during all conditions. Differences in variability were analysed using repeated measures ANOVA with Bonferroni corrections

 

Discussion

In this study, we found that sensor-measured gait variability after two years could be predicted by a composite score of muscle strength, based on z-scores from handgrip strength, isometric knee extension strength and the 30 second chair rise test, independently of gait speed.
The associations between muscle strength and gait variability has not been studied extensively. Shin and co-authors found that lower limb muscle quality (the proportion of the cross-sectional area that is free from fat), but not isometric lower limb strength was associated with spatial and to some extent temporal gait variability (16) and Callisaya and co-authors found that isometric knee extension strength was associated with temporal gait variability (17). In both these studies, gait variability was measured with an electronic gait mat, and results are therefore not directly comparable to our findings. However, it appears that maximal, isometric muscle strength and muscle quality plays a role in gait variability, although walking is an activity that does not require maximal strength (18). Previous research has focused on the role of the central nervous system in gait variability, specifically deterioration of areas associated with sensorimotor integration and coordination (19). Muscle strength may therefore primarily be an indication of general health, fitness and a physically active lifestyle (20), and gait variability may be lower in fit and healthy people (21). Other measurements of submaximal muscle functioning, such as electromyography may give more information about the role of specific muscle activation in gait variability (22, 23).
The rationale for including other walking conditions than just preferred speed walking was that the participants should be challenged more, and to explore whether gait performance that is more marginal would be more revealing of functional status. However, fast speed walking or uneven surface walking appeared not to have any closer association with muscle strength than preferred speed walking. It could be that fast and uneven surface walking conditions were not more challenging than preferred speed walking, and also that muscle strength was sufficient during all walking conditions, and that extra maximal strength gave little extra benefit (18). Two-year variability during dual task-walking was not associated with the baseline strength composite score. We suggest that variability during this walking condition depends primarily on attentional and executive resources (24). Baseline tests of cognitive or executive function would possibly have been better predictors of change in gait variability under these conditions. Further, during preferred and fast speed walking, movement in the ML direction is more variable than in the other directions (figure 2). Walking is partially a ballistic movement, with propulsion produced to a great extent by elastic and passive (inertia) forces, with muscle force being necessary primarily in step-to-step transitions, and then for controlling sideways movement. Thus variability in the ML direction tends to be greater than in the AP and V directions, and is generally seen as a sign of healthy and adaptive gait (25, 26).
Gait variability can be seen as an indication of  balance control during walking (5), and gait variability measured with footfall analysis has been found to be associated with fall risk (7). As pointed out above, variability measures from trunk accelerations may not be entirely comparable with footfall variability. Doi and co-authors found that a measure of walking smoothness (harmonic ratios), derived from trunk accelerations, was predictive of falls (27). While this is a different metric than what we have used in our study, the two are related (28). As such, it is not implausible that gait variability as described in our study is also a predictor of falls, but further studies are needed to ascertain this.
In this study, we chose to make a composite score of the muscle strength tests. It could be argued that this makes comparisons difficult with other studies using separate muscle strength tests. However, we argue that the three tests we use measure different aspects of strength: Upper and lower body strength, as well as dynamic whole-body movements and isolated isometric limb strength. By combining these different aspects in one composite measure, we believe that we give a more representative picture of general strength.

The majority of the participants had one or more chronic diseases and used medications regularly. It is unclear how disease and medication use may have impacted gait in the participants, but it is assumable that for example osteoarthritis, which 11 of the participants reported having, could affect walking. Barden and co-authors found that gait variability was higher in older adults with knee osteoarthritis than age-matched asymptomatic control (29). Further, Donoghue and co-authors found that antidepressant use, which four of the participants reported, was associated with gait deficits (30). Further studies with larger sample sizes should be undertaken to investigate the impact of specific disease on gait in community-living older adults.
The results are from a relatively small group of community-living older adults who were able and motivated to participate in the study. Generalizability can thus be questioned. In our study, the participants had an average of 1.58 chronic diseases and used an average of 2.14 medications regularly, which resembles what has been reported in larger studies (31). Our results were based on self report and should be interpreted with some caution.  Grip strength has also been reported in other studies, allowing for comparison: Dodds et al reported grip strengths of 23-21 kg for women and 35-39 kg for men in a similar age group (32) which is somewhat higher than what we found. We therefore suggest that the participants in our study share some features with larger and more representative studies, and that our findings have some degree of generalizability.
We conclude that a composite strength score at baseline was associated with gait variability after two years in our sample of community-dwelling older adults, and we suggest that muscle strength in our sample was a general indicator of health and fitness. Further research should be undertaken to pinpoint muscle strength cut offs that may identify persons at risk of gait deterioration.

 

Funding: This study was funded by the Norwegian Fund for Post-graduate Training in Physiotherapy
Conflicts of Interest: The authors declare that they have no conflict of interest.

 

References

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12.    Moe-Nilssen R, Helbostad JL. Estimation of gait cycle characteristics by trunk accelerometry. J Biomech. 2004;37(1):121-6.
13.    Jones CJ, Rikli RE, Beam WC. A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Res Q Exerc Sport. 1999;70(2):113-9.
14.    Turner A. Total Score of Athleticism: a strategy for assessing an athlete’s athleticism; 2014.
15.    Onder G, Penninx BW, Ferrucci L, Fried LP, Guralnik JM, Pahor M. Measures of physical performance and risk for progressive and catastrophic disability: results from the Women’s Health and Aging Study. J Gerontol A Biol Sci Med Sci. 2005;60(1):74-9.
16.    Shin S, Valentine RJ, Evans EM, Sosnoff JJ. Lower extremity muscle quality and gait variability in older adults. Age Ageing. 2012;41(5):595-9.
17.    Callisaya ML, Blizzard L, McGinley JL, Schmidt MD, Srikanth VK. Sensorimotor factors affecting gait variability in older people–a population-based study. J Gerontol A Biol Sci Med Sci. 2010;65(4):386-92.
18.    Buchner DM, Larson EB, Wagner EH, Koepsell TD, de Lateur BJ. Evidence for a non-linear relationship between leg strength and gait speed. Age Ageing. 1996;25(5):386-91.
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29.    Barden JM, Clermont CA, Kobsar D, Beauchet O. Accelerometer-Based Step Regularity Is Lower in Older Adults with Bilateral Knee Osteoarthritis. Front Hum Neurosci. 2016;10:625.
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DECREASED HANDGRIP STRENGTH IS ASSOCIATED WITH IMPAIRMENTS IN EACH AUTONOMOUS LIVING TASK FOR AGING ADULTS IN THE UNITED STATES

 

R. McGrath1, K. M. Erlandson2, B.M. Vincent3, K.J. Hackney1, S.D. Herrmann4, B.C. Clark5,6,7

 

1. Department of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, USA; 2. Department of Medicine, Divisions of Infectious Diseases and Geriatric Medicine, University of Colorado-Anschutz Medical Campus, Aurora, CO, USA; 3. Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA; 4. Sanford Research, Sioux Falls, SD, USA; 5. Ohio Musculoskeletal and Neurological Institute, Ohio University, Athens, OH, USA; 6. Department of Biomedical Sciences, Ohio University, Athens, OH, USA; 7. Department of Geriatric Medicine, Ohio University, Athens, OH, USA.
Corresponding author: Ryan McGrath, PhD, Department of Health, Nutrition, and Exercise Sciences, North Dakota State University, NDSU Dept. 2620, PO Box 6050, Fargo, ND 58108-6050, Email: ryan.mcgrath@ndsu.edu
J Frailty Aging 2019;in press
Published online December 28, 2018, http://dx.doi.org/10.14283/jfa.2018.47

 


Abstract

Objectives: The primary purpose of this study was to determine the time-varying associations between decreased handgrip strength (HGS) and individual instrumental activities of daily living (IADL) impairments for a nationally-representative sample of aging adults in the United States. Design: Longitudinal-Panel. Setting: Detailed interviews were completed in person and core interviews were typically completed over the telephone. Participants: A total of 15,336 participants aged at least 50 years who participated in the 2006 wave of the Health and Retirement Study were followed biennially for 8-years. Measurements: A hand-held dynamometer assessed HGS and performance in IADLs were self-reported. Results: Every 5-kilogram decrease in HGS was associated with an increased odds ratio for the following IADL impairments: 1.11 (95% confidence interval (CI): 1.09, 1.13) for using a map, 1.10 (CI: 1.07, 1.12) for grocery shopping, 1.09 (CI: 1.05, 1.14) for taking medications, 1.07 (CI: 1.05, 1.09) for preparing hot meals, 1.06 (CI: 1.04, 1.08) for managing money, and 1.05 (CI: 1.02, 1.09) for using a telephone. Conclusions: Decreased HGS was associated with each IADL impairment, and slightly different associations were observed in individual IADL tasks for aging adults in the United States. Our findings suggest that decreased HGS, which is reflective of reduced function of the neuromuscular system, is associated with diminished performance in autonomous living tasks during aging. Losses in HGS may lead to the development of an IADL impairment. Therefore, health-care providers working with aging adults should utilize measures of HGS as a screening tool for identifying future deficits in neuromuscular functioning. Interventions designed to preserve IADLs in aging adults should also include measures of HGS for detecting early changes in IADL capacity, and intervening at the onset of HGS declines may help aging adults retain their ability to live autonomously.

Key words: Cognition, geriatrics, motor skills, muscle strength, muscle weakness


 

Introduction

Handgrip strength (HGS) is commonly used for clinical and population screenings of overall muscle strength in aging adults (1). While decreased HGS is typically ascribed to reductions in muscle mass, there is evidence that suggests declines in HGS are sensitive to the integrity of the nervous system centers that mediate the control of coordinated movement (2). For example, the force generated during a maximum voluntary grip force task is around half of what would be expected if the skeletal musculature itself were fully activated by the nervous system (3, 4), due to reduced neural drive to the muscles (5). Moreover, deficits in cognitive and motor performance coexist during aging, and are important mechanisms for accelerating the disabling process (6). Therefore, it is plausible that decreased HGS is associated with tasks that require higher neuropsychological functioning and relatively little muscular force production, such as several instrumental activities of daily living (IADL).
Assessments of IADLs examine a person’s ability to perform tasks that are necessary for independent living, and the ability to perform IADLs are dependent on cognitive, motor, and perceptual capabilities (7). Given that age-related weakness, as measured by HGS, is reflective of both decreased muscle strength and nervous system integrity, we suspect that measures of HGS may help to identify future deficits in IADLs for aging adults, including those that require low levels of muscle force generation. Accordingly, the primary purpose of this investigation was to determine the time-varying associations between decreased HGS and individual IADL impairments for a nationally-representative sample of aging adults in the United States. Additionally, we also sought to examine the role of cognitive functioning as an influential factor in these associations for a secondary purpose.

 

Methods

Participants

Those aged 50 years and older who participated in the 2006 wave of the Health and Retirement Study (HRS) were followed biennially for 8-years (n=18,469). Beginning in the 2006 wave, half of the participants alternated completion of the core interviews and detailed face-to-face interviews. Sample weights are supplied to account for the multi-stage, area probability design and they were utilized in the analyses. Participants from the HRS provided written informed consent and study protocols were approved by the University’s Behavioral Sciences Committee Institutional Review Board. Details for the HRS have been previously published (8).

Outcome Variable

At each wave, participants reported their ability to perform the following IADLs: use a map, prepare hot meals, take medications, manage money, use a telephone, and shop for groceries. Those indicating difficulty or an inability to complete an IADL were regarded as impaired for that specific task.

Exposure Variable

A Smedley spring type hand-held dynamometer (Scandidact, Denmark) was used to measure maximal HGS. Details for the HGS test protocol are explained elsewhere (9). Data for HGS from either the 2006 and 2008 waves, or 2010 and 2012 waves were concatenated because HGS measurements were a part of the detailed face-to-face interviews.

Covariates

Cognitive functioning was evaluated with a series of tests from the modified Telephone Interview of Cognitive Status questionnaire (10). A 27-point composite scale was used for those aged under 65-years and respondents with scores ≤11 were considered as having a cognitive impairment (11). For those aged at least 65-years, a 35-point composite scale was used and respondents with a score of ≤10 were considered as having a cognitive impairment (12). Proxy respondents were excluded (n=2,735) because the ability to perform certain IADLs were a part of the cognitive functioning assessments for proxies.
Morbidity was collected by self-report of health-care provider diagnosed hypertension, diabetes, cancer, lung disease, heart condition, stroke, psychiatric problems, and arthritis. A morbidity count of affirmative diagnoses was summed at each wave and included in the analyses. Participants also reported at each wave if they had ever smoked 100 cigarettes or more in their lifetime, and if they were currently smoking cigarettes. Mental health was assessed at each wave with the 8-item Center for the Epidemiologic Studies Depression (CES-D) scale. Continuous scores were used in the analyses. Participants rated their perceived health (“excellent”, “very good”, “good”, “fair”, “poor”) at each wave with a single-item measure. Age, sex, race and ethnicity (Black, Hispanic, White), height, and body mass were also self-reported. Body mass index (BMI) was calculated as body mass divided by height in meters-squared.

Statistical Analysis

Separate hierarchical logistic regression models evaluated the time-varying associations between decreased HGS and impairments in each IADL. Demographic variables including sex, race and ethnicity, and age were controlled for in the crude models. Morbidity-related variables including smoking history, current smoking status, CES-D scores, self-rated health, the number of diagnosed morbidities, and BMI were subsequently added to the crude models (partially-adjusted models). Then, cognitive impairments were added to the partially-adjusted models (fully-adjusted models). The fully-adjusted models were used for determining the associations between decreased HGS and impairments in each IADL. Covariates included in the models were determined a priori by investigators because they were viewed as being influential for our results, and the time-varying analyses were calculated between each wave (2006, 2008, 2010, 2012, and 2014 waves). Those with missing covariates for all waves were excluded (n=398).
A sensitivity analysis was performed to examine the potential confounding effect of sex. The fully-adjusted hierarchical logistic models were stratified by sex, and if the estimates for each IADL outcome in the sex stratified models changed by >10% compared to the non-sex stratified models, there was evidence of confounding for sex in the models (13). Likewise, an additional sensitivity analysis was performed to examine the potential confounding effect of age. The fully-adjusted hierarchical logit models were stratified by age (middle-aged: 50-64 years; older adult: ≥65 years), and the estimates of the age stratified models were compared to the non-age stratified models using the same >10% criteria (13).

 

Results

Of the 15,336 participants included from the 2006 wave, the majorities were female (60.0%) and White (81.4%). At each wave, the highest percentage of participants had an IADL impairment in reading a map; whereas, an IADL impairment in taking medications had the lowest percentage. Additional participant characteristics are detailed in Table 1 and a flow chart of exclusions is presented in Appendix 1. To compare descriptive variables between waves, Appendix 2 provides the means and 95% confidence intervals (CI). The number of missing observations at each wave for variables included are shown in Appendix 3.

Table 1 Descriptive Characteristics of the Participants

Table 1
Descriptive Characteristics of the Participants

Note: Results are Presented as Median (Quartile 1, Quartile 3) or Frequency (Percentage) as Indicated. IADL=instrumental activities of daily living; kg=kilogram; kg/m2=kilograms per meters-squared.

 

Table 2 summarizes the results of the crude, partially-adjusted, and fully-adjusted hierarchical logit models for the time-varying associations between decreased HGS and individual IADL impairments. When adding cognitive impairments to the partially-adjusted models (fully-adjusted models), the odds ratios were attenuated by 0.03 for using a telephone, 0.02 for taking medications, and 0.01 for using a map, preparing hot meals, managing money, and grocery shopping.
The results of the fully-adjusted hierarchical logit models determined that every 5-kilogram decrease in HGS was associated with increased odds for each IADL impairment: 1.11 (CI: 1.09, 1.13) for using a map, 1.10 (CI: 1.07, 1.12) for grocery shopping, 1.09 (CI: 1.05, 1.14) for taking medications, 1.07 (CI: 1.05, 1.09) for preparing hot meals, 1.06 (CI: 1.04, 1.08) for managing money, and 1.05 (CI: 1.02, 1.09) for using a telephone. Complete results for the crude, partially-adjusted, and fully-adjusted models are presented in Appendices 4, 5, and 6, respectively. The estimates for both the sex and age stratified models did not change by >10% when comparing to the estimates of the non-sex and age stratified models, suggesting sex and age were not confounding (Appendices 7 and 8).

Table 2 Results for the Time-Varying Associations Between Decreased Handgrip Strength and Individual IADL Impairments

Table 2
Results for the Time-Varying Associations Between Decreased Handgrip Strength and Individual IADL Impairments

Note: Model 1 (crude models) controlled for sex, race and ethnicity, and age. Model 2 (partially-adjusted models) controlled for Model 1 + body mass index, morbidity, depression score, current smoking status, smoking history, and self-rated health. Model 3 (fully-adjusted models) controlled for Model 2 + cognitive impairments. CI=95% confidence interval; HGS=handgrip strength; IADL=instrumental activities of daily living; OR=odds ratio. 

 

Discussion

This investigation revealed that decreased HGS was associated with increased odds for individual IADL impairments, and slightly different associations were seen in each IADL for aging adults in the United States. Including cognitive impairments in our models attenuated the estimates by 1-3%. These findings suggest that age-related declines in HGS may lead to impairments in tasks that require strong neuropsychological and motoric functioning, including IADLs that only require low levels of muscle force generation.
Age-related decreases in muscle mass and strength have been strongly linked to a range of health-related conditions (1, 14). The general understanding for findings of this nature have been that muscle weakness, from sarcopenia and dynapenia, impairs a person’s ability to perform activities that require higher amounts of muscle force generation (15, 16). Accordingly, HGS is commonly interpreted as a measure of skeletal muscle function. The interpretation of HGS as a simple measure of skeletal muscle function could be viewed as an oversimplification, as there is evidence that HGS is strongly determined by the function of the nervous system (2). For instance, the maximum force that can be produced by each finger decreases in proportion to the number of other fingers that are engaged simultaneously, such that when four fingers contribute to the grip task, the maximum force that can be generated by each digit is typically less than half that produced when engaged in isolation (i.e., force deficit) (4, 17). This HGS force deficit is larger in aging adults compared to younger adults (4, 18). As such, declines in HGS are sensitive to the integrity of the nervous system centers that mediate the control of coordinated movement.
As adults age, the cognitive demand for completing motor tasks increases (19), and declines in HGS may help to identify early cognitive and motor defects (2). Given that the ability to execute IADLs is dependent on cognitive and motor capabilities (7), this may explain why our findings demonstrate that decreased HGS was associated with impairments in tasks that require a low amount of muscular force output. We believe our results support the notion that declines in HGS should be considered as a measure that is reflective of diminished musculoskeletal, neuromuscular, and nervous system function (or at least the motoric system).
Our findings also demonstrate that decreased HGS was associated with IADLs that require larger muscle force generation such as grocery shopping. The ability to shop for groceries is mostly driven by physical abilities such as mobility, lifting, and carrying items (20). This result is compatible with the results of other investigations suggesting decreased HGS is associated with physically driven tasks such as individual ADLs and gait speed (21, 22). Therefore, having an IADL impairment for grocery shopping may place aging adults at greater risk for functional declines. Health-care providers with aging adult patients should consider using HGS measurements as a screening tool for identifying future declines in neuromuscular functioning. Future research should work toward expanding HGS methods while also developing innovative strategies for assessing the link between HGS and neural function.
Cognitive declines during aging may also influence performance in autonomous living tasks. Several of the tasks included in IADL assessments require higher neuropsychological functioning, and persons with cognitive impairments tend to experience IADL deficits (23). For example, IADLs are helpful for detecting early cognitive declines (7), and mild cognitive impairments often lead to dementia (24). After adding cognitive impairments to our models, the odds ratios for the association between decreased HGS and each IADL impairment declined by a small percentage. Although our results suggest that decreased HGS can be used to help identify reduced motor and neural system function, cognitive functioning factors into the associations between HGS and IADLs to a much lesser extent, likely because IADLs are already cognitively driven. Future investigations should consider how cognitive functioning factors into the associations between HGS and more physically driven tasks.
These findings provide continued support for the belief that muscle strengthening, motor coordination, and agility enhancing activities are critical for maintaining functional capacity during aging. Participation in muscle strengthening activities has demonstrated promise for preserving muscle strength, motor performance, cognitive functioning, and neural integrity (25). Interventions aiming to preserve IADLs should be multidisciplinary in nature, wherein factors for maintaining motor performance, including physical, social, and mental health activities are incorporated. Interestingly, engaging in muscle strengthening activities has shown potential for improving spatial awareness in older adults by also improving brain health (26). Specifically, muscle strengthening activities may prevent age-related atrophy of the temporal lobe, which is important for vision, sensory input, and comprehension (27). The increased blood flow and usage of nutrients in the blood from participating in muscle strengthening activities may lead to improved neurogenesis and neurotransmission, thereby ameliorating spatial awareness and brain health (26, 28, 29). Intervening at the onset of HGS declines may help to preserve muscle strength, cognitive functioning, motor performance, and the ability to live independently.
There are limitations of this work that should be mentioned. Self-report bias may have created underestimations for our results because respondents reported IADL performance.  Another limit of our study was the progressive reduction of the sample size over time due to people who dropped-out or died during the examination period. Participants in the 2006 wave were followed biennially for 8-years and if there were missing covariates for a particular wave, those data were excluded from the models for that wave. However, multilevel models can overcome intermittent missing data between waves and participant drop-out was <5% between waves (30). Although our sensitivity analyses revealed that sex was not confounding for our results, it is still important to consider the potential role of gender norms when evaluating IADLs in aging adults.

 

Conclusions

Decreased HGS was associated with each IADL impairment, and slightly different associations were observed for impairments in individual IADLs, including those that not only require a minimal amount of muscle force generation, but rather motor coordination and cognitive functioning. Adding cognitive impairments to our models reduced the magnitude of the association between decreased HGS and individual IADL impairments by a small amount. Our findings support the notion that decreased HGS should be considered a measure that is reflective of both reduced skeletal muscle and nervous system function.

 

Acknowledgements: BCC is supported, in part, by the National Institute on Aging (R01AG044424).
Conflicts of Interest: BCC has received research funding from the National Institutes of Health, Regeneron Pharmaceuticals, Astellas Pharma Global Development, Inc., RTI Health Solutions, Ohio Department of Higher Education, and the Osteopathic Heritage Foundations. In the past 5-years BCC has received consulting fees from Regeneron Pharmaceuticals, Abbott Laboratories, and the Gerson Lehrman Group. Additionally, BCC is co-founder with equity and scientific director of AEIOU Scientific, LLC. The other authors report no conflicts of interest.

 

APPENDIX

 

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THE EFFECT OF HIGH DOSE VITAMIN D3 ON PHYSICAL PERFORMANCE IN FRAIL OLDER ADULTS. A FEASIBILITY STUDY

 

N.W. BRAY1,2,3, T.J. DOHERTY1,3,6,7,8, M. MONTERO-ODASSO1,2,3,4,5

 

1. Faculty of Health Sciences, School of Kinesiology, Western University, London, ON, Canada; 2. Gait and Brain Lab, Parkwood Institute, London, ON, Canada; 3. Lawson Health Research Institute, London, ON, Canada; 4. Schulich School of Medicine and Dentistry, Department of Medicine and Division of Geriatric Medicine, Western University, London, ON, Canada; 5. Schulich School of Medicine and Dentistry, Department of Epidemiology and Biostatistics, Western University, London, ON, Canada; 6. Neuromuscular Function Lab, Parkwood Institute, London, ON, Canada; 7. Schulich School of Medicine and Dentistry, Department of Clinical Neurological Sciences, Western University, London, ON, Canada; 8. Schulich School of Medicine and Dentistry, Department of Physical Medicine and Rehabilitation, Western University, London, ON, Canada.
Corresponding author: Dr. Manuel Montero-Odasso, Gait and Brain Lab, Parkwood Institute, 550 Wellington Road, Room A3-116, London, ON, Canada, N6C 0A7, E-mail: mmontero@uwo.ca, Fax: (519) 685 0493.

J Frailty Aging 2018;in press
Published online July 5, 2018, http://dx.doi.org/10.14283/jfa.2018.18

 


Abstract

Abstract: Background: Vitamin D deficiency is ubiquitous in frailty but the effectiveness of vitamin D supplementation to improve outcomes in frail individuals is unclear. It has been postulated that higher than the current recommended doses (800 IU/day) may be needed to achieve a neuromuscular effect in frail individuals. Objectives: 1) determine if 4000 IU per day of vitamin D3 is safe for frail older adults; and 2) establish the efficacy of this dose to improve physical performance outcomes in this population. Design: Open-label, feasibility study. Setting: Community retirement centre. Participants: 40 older adults with frail or pre-frail characteristics. Intervention: 4000 IU of vitamin D3 and 1200 mcg of calcium carbonate daily for four months. Measurements: Physical performance (grip strength, gait speed and short physical performance battery score), cognitive health and vitamin D and iPTH serum levels before and after the intervention. Results: Frail individuals improved short physical performance battery score (1.19, p = 0.005), fast gait speed (4.65, p = 0.066) and vitamin D levels (7.81, p = 0.011). Only frail females made a significant improvement in grip strength (1.92, p = 0.003). Stratifying the sample by baseline vitamin D levels revealed that participants with vitamin D insufficiency (≤ 75 nmol/L) significantly improved short physical performance battery score (1.06, p = 0.04), fast gait speed (6.28, p = 0.004) and vitamin D levels (25.73, p = <0.0001). Pre-frail individuals, as well as those with sufficient vitamin D levels (> 75 nmol/L) made no significant improvement in any outcome. Conclusions: Vitamin D supplementation using 4000 IU/daily is safe and has a modest beneficial effect on physical performance for frail individuals and those with insufficient vitamin D levels. Participants with vitamin D insufficiency (≤ 75 nmol/L) showed greater benefits. Our feasibility study provides results to help calculate effect size for a future RCT.

Key words: Aged, Gait, Frailty, Vitamin D, Early Medical Intervention, Muscle Strength.


 

Introduction

Frailty is recognized as a state of mild to severe vulnerability caused by a reduction across various physiological systems which places the individual at increased risk for disease and disability (1). The expected growth of the aging population will result in a rapid increase in the absolute prevalence of this geriatric syndrome over the next 30 years (2), placing a significant financial burden upon healthcare systems. Frailty is an independent predictor of hospitalization, institutionalization, falls, worsening health status, and even mortality but it does not mark the end of life (3,4). Frailty exists on a spectrum (non-frail, pre-frail and frail) and there is even heterogeneity in pure frail individuals (5). However, transitions between states are not unidirectional.
Physical exercise (6,7) and nutritional supplementation (8) are the only interventions to consistently delay or reverse frailty. Sarcopenia and osteoporosis are two of several potential modifiable factors that may indirectly improve frailty status, although treatments remain inconclusive (9).
Vitamin D deficiency is ubiquitous in frailty (10), and it has been associated with slowing gait (11,12), higher comorbidities (13), falls (14), brain health (15) and mortality (16). However, the efficacy of vitamin D supplementation to improve neuromuscular outcomes in frail individuals is unclear. A meta-analysis conducted by our group concluded that at least 800-1000 IU in daily doses demonstrates beneficial effects on balance and muscle strength in healthy and clinical populations (17), showing more benefits with higher doses. This meta-analysis suggested that doses higher than the minimum current recommendations (400 to 800 IU/day; 18) for bone health, may be needed to achieve a neuromuscular effect in frail individuals due to their higher risk of vitamin D deficiency.
Only one study has performed a vitamin D intervention utilizing a daily dosing strategy (1000-2000 IU/day) greater than the current recommended amount for participants classified according to a frailty identification tool (19). However, participants were exclusively pre-frail, doses varied based upon baseline vitamin D levels and the intervention was completed as an 8-week run-in phase to a resistance training program.
Therefore, the purpose of our study was: 1) to determine if an even greater dose (4000 IU/day) of vitamin D was safe and feasible for frail and pre-frail older adults; and 2) to establish the efficacy of this dose to improve neuromuscular physical performance outcomes in this population. We hypothesized that 4000 IU/day of vitamin D would: 1) be feasible and safe for frail and pre-frail older adults; and 2) lead to an improvement in gait, strength and short physical performance battery (SPPB) scores, as well as cognition.

 

Methods

Design and Participants

This was an open-label, interventional study, that included 40 older adults with frailty characteristics. Sample size was estimated to detect a significant increase in gait speed, 10 cm/s after intervention, assuming a power of 80%, ∞ of 5% and dropout rate of 10%. Participants were recruited from the Cherryhill naturally occurring retirement centre, a 13-building apartment complex in London, Ontario housing 2,500 older adults (mean age = 79.53 ± 9.53 years).
In addition to being frail or pre-frail, inclusion criteria were the following: 75 years of age or more; male or female; able to ambulate 10 meters with or without a mobility aid; and proficiency in English. Individuals were excluded if they: were taking vitamin D doses >1000 IU/day within the last six months; had a hip or knee fracture/replacement in the preceding six months; were diagnosed with dementia; had a history of severe bone disease (osteomalacia); had overactive parathyroid glands (hyperparathyroidism) or severe kidney problems that require dialysis (renal insufficiency); and were suffering from any neurological disorder (i.e. stroke) with residual motor deficits affecting gait.
Ethics approval was obtained from the Western University’s Ethics Board for Health Sciences Research involving Human Subjects (Review Number: 15663). All participants read and signed a letter of informed consent during enrollment.

Frailty Status Ascertainment

Frailty status was ascertained using a modified (4) Frailty Phenotype (20), which has been previously validated (21, 22). In brief, slow gait speed was met if the participant walked below one meter per second (1m/sec) at a usual and comfortable pace. Previous research suggests gait speed below 1m/sec indicates risk of adverse health outcomes (23, 24). Low physical activity criterion was operationalized using the Physical Activity Scale for the Elderly (PASE). PASE scores less than 64/52 for men/women indicated a positive response of low physical activity. The muscle weakness criterion was met when grip strength in the dominant hand was less than or equal to cut-off points used in the original Frailty Phenotype (20). The exhaustion criterion was evaluated using two questions from the Center for Epidemiologic Studies Depression Scale; participants that confirmed everything they did was an effort or that they felt they could not get going in the previous two months, indicated a positive response. Participants met the weight criteria if they had unintentionally lost more than five kilos in the previous 12 months. A total score for frailty status was then calculated as the sum of positive findings. Individuals were then categorized into one of three frailty categories based on the total frail score, as follows: frail, score ≥3; pre-frail, score of 1–2; and non-frail, score of 0.

Intervention

Participants consumed 4000 IU of vitamin D3 (cholecalciferol) and 1200 micrograms (mcg) of calcium carbonate upon waking, every day for four months. Tablets were provided in a monthly blister package prepared by our research pharmacist. At the end of every month of enrollment, a research assistant completed a check-in with each participant. During check-ins, tablets from “missed” days were collected and tabulated, and the next month supply was delivered. These procedures helped to promote adherence and compliance. Information about falls, adverse events related to the intervention and general well-being were also collected during check-ins. For the duration of the intervention, participants were asked to maintain their normal diet and routine, and not consume any additional vitamin D and/or calcium.

Assessment Timeline

Assessments were completed at baseline (T0) and post-intervention (T4) during the four months of follow-up.

Medical and Cognitive Assessments

Information pertaining to sociodemographic characteristics, previous falls, fractures, prescribed medications, comorbidities and anthropometrics were recorded and confirmed using electronic medical records. A disability scale developed for community-based cohorts evaluated functional capacity in basic activities of daily living. Summed disability scores ranged from 0-16, with higher scores equating to greater disability
Cognition was assessed via the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) questionnaire. Alternate MoCA versions were utilized during follow-up assessments to prevent a learning effect.

Physical Performance Assessments

Grip strength was assessed using a hand-held dynamometer (Jamar, Sammons Preston, Bolingbrook, IL), in a seated position, with the shoulder neutrally rotated and elbow flexed to 90˚ so that the lower part of the contracting arm rested upon the arm of the chair. Participants were instructed to not lift their arm from the arm of the chair while contracting or the repetition would be repeated. The result of this test was used in the grip strength criteria for frailty ascertainment. Knee extension strength was evaluated using a Biodex System 3 Dynamometer (Biodex Medical Systems Inc., Shirley, NY) via a standardized protocol by Bassey and Short (1990). Participants performed three contractions on the dominant hand and leg, and the average was used for data analysis.
Gait performance was assessed using the six-meter GAITRite Portable Walkway System (CIR Systems Inc., Franklin, NJ). The GAITRite software collects and analyzes the imprint of each foot fall in real-time to calculate the participant’s gait speed. Participants performed one untimed practice trial before completing three trials at both a usual and fast pace; these walking conditions have been previously described elsewhere (22). Participants started/finished each walk one meter before/after either walkway end to avoid recording acceleration/deceleration phases.
General physical performance was assessed via the short physical performance battery (SPPB) protocol, a standardized performance test applied in research and geriatric settings, which characterizes older adults across a broad spectrum of lower extremity function (26). The SPPB requires individuals to complete a: 1) hierarchy of balance tasks; 2) repeated five-time sit-to-stand task; and 3) a 2.4 meter walking course at their “normal speed”. Individuals are assigned a score of 0-4 for all tasks, for a total possible score ranging from 0-12; higher scores indicate greater physical performance and thus, functional independence.

Vitamin D, iPTH and Calcium Serum Levels

Venous blood samples were collected for the measurement of 25(OH) vitamin D, intact parathyroid hormone (iPTH) and calcium serum levels. Specimens were stored at -82° C as aliquots, immediately after centrifugation. Serum 25(OH) vitamin D was measured using a specific RIA (Diasorin Inc., Sallugia, Italy). Serum levels of iPTH were determined by a two-site chemiluminescent ELISA (Alpco Ltd., Salem, NH; range:10-55pg/ml, sensitivity:1.57 pg/ml). Serum ionized calcium levels were evaluated via the Kodak method® (Kodak, USA).

Primary Outcome Measure

The primary outcome measures were gait speed, muscle strength, and SPPB score. The secondary outcome was the effect of the intervention upon cognitive status.

Statistical Analysis

Demographics and clinical characteristics are summarized using either means and standard deviations or frequencies and percentages, as appropriate. A one-way analysis of variance or Pearson chi-square analysis compared baseline characteristics. A one-way analysis of covariance assessed primary and secondary outcome measures, stratified by frailty status (pre-frail or frail) and baseline vitamin D levels (> or ≤ 75 nmol/L), and adjusted for relevant confounders, including age, sex, baseline vitamin D levels and number of comorbidities and medications. All statistical tests were two-tailed and a p-value ≤ 0.05 indicated significance. Analyses were made using SPSS version 23.0 (SPSS Inc., IBM Corporation, Chicago, IL).

 

Results

Forty older adults were included in this study. Participants were mostly female (78%), and had an average age, body mass index and years of education of 84.20 (±4.88), 25.64 (±3.70) and 12.38 (±3.07), respectively. Baseline vitamin D levels were insufficient (≤ 75 nmol/L) or sufficient (> 75 nmol/L) in 16 and 24 participants, respectively. Coincidently, sixteen participants were pre-frail (1-2 indicators) and 24 were frail (≥ 3 indicators). Slow gait was the most common indicator of frailty, followed by weakness, exhaustion, low activity and weight loss. Baseline participant characteristics, stratified by vitamin D levels, were statistically similar (Table 1).

Table 1 Baseline characteristics (n=40) stratified by baseline vitamin D levels (Insufficient and Sufficient)

Table 1
Baseline characteristics (n=40) stratified by baseline vitamin D levels (Insufficient and Sufficient)

Note: *ANOVA, Pearson chi-square analysis as appropriate. a, n=22.

 

Figure 1 Percentage change in measures with significant change, stratified by frailty and vitamin D status

Figure 1
Percentage change in measures with significant change, stratified by frailty and vitamin D status

PASE = Physical Activity Scale for the Elderly; SPPB = Short Physical Performance Battery; Vit D = vitamin D levels; FG = fast gait speed; nmol/L = nanomoles per litre; * = p-value <0.05; † = p-value <0.01;  ‡ = p-value <0.0001.

 

Outcome variables post-intervention, stratified by frailty status and baseline vitamin D levels, are displayed in Table 2 and 3, respectively. Frail individuals showed significant improvement in SPPB score, PASE score and vitamin D levels (Figure 1). Additionally, fast gait speed was trending (p = 0.066) towards significance (Table 2). Only frail females made a significant improvement in grip strength (p = 0.003; not shown in table). Pre-frail individuals exhibited no significant improvement in any outcome variable. Individuals with insufficient vitamin D levels showed significant improvement in SPPB score, fast gait speed and vitamin D levels (Figure 1). Individuals with sufficient vitamin D levels demonstrated no significant improvement in any outcome variable (Table 3). The dosing strategy did not lead to an adverse event, nor to the development of hypercalcemia.

Table 2 Changes in outcome measures after intervention (T4), stratified by baseline (T0) frailty status

Table 2
Changes in outcome measures after intervention (T4), stratified by baseline (T0) frailty status

Note: iPTH = intact parathyroid hormone; UG = usual gait; FG = fast gait; N = newton; nmol/L = nanomoles per litre; pg/ml = pictograms per millilitre; mmol/L = millimoles per litre; cm/sec = centimeters per second.

 

Table 3 Changes in outcome measures after intervention (T4), stratified by baseline (T0) vitamin D levels

Table 3
Changes in outcome measures after intervention (T4), stratified by baseline (T0) vitamin D levels

Note: iPTH = intact parathyroid hormone; UG = usual gait; FG = fast gait; N = newton; nmol/L = nanomoles per litre; pg/ml = pictograms per millilitre; mmol/L = millimoles per litre; cm/sec = centimeters per second.

 

Discussion

Vitamin D3 supplementation in a daily dose of 4000 IU for four months results in significant improvement in SPPB and PASE score in frail individuals. Grip strength and fast gait speed also improves in frail individuals but only the former is significant, and only in females. When stratifying the sample by baseline vitamin D levels, we found that SPPB score and fast gait speed significantly improve for those with insufficiency. No participant, regardless of baseline vitamin D or frailty status, experienced an adverse outcome.
These results suggest improvement in lower extremity function for those with greater deficits i.e. frail and insufficient vitamin D levels. These groups experienced a clinical (27) and statistically significant improvement in SPBB score. These changes have meaningful implications as SPPB score has been associated with disability, institutionalization and falls (27). Improvement in lower extremity function is further supported by the observed increases in knee strength for those with insufficient vitamin D levels, albeit not significant.
Our results also suggest improvement in physical reserve. Although all participants were instructed to maintain their normal routine during the intervention, frail individuals made a significant improvement in PASE score. Vitamin D supplementation may have helped to partially alleviate the significant deficits that are commonly associated with frailty. Previous research has highlighted that vitamin D supplementation may be a restorative hormone given its positive impact upon postural sway, falls risk, and bone fractures (9). Thus, the intervention may have led to greater functional capacity, ability to perform activities of daily living and possibly even exercise, creating a positive feedback loop leading to enhanced overall fitness.
Improvement in physical reserve is supported further by the observed change in fast gait speed. Fast gait speed significantly improved in those with insufficient vitamin D levels and was trending towards a statistically significant improvement in frail participants. The ability to alter walking speed from a usual to fast pace has been termed walking speed reserve (28). A greater difference between these walking conditions demonstrates greater reserve and may indicate better physiological and cognitive abilities (28).
The significant improvement observed in grip strength for only frail females post-intervention is likely attributed to the male-female health-survival paradox; a phenomenon where females become frail earlier, yet live longer than males (29). It has been shown that females have higher frailty scores when compared to men across seven different frailty scales (30). Thus, onset and progression of the syndrome follow sex-specific pathways and ultimately, further complicate this geriatric syndrome.
Previous research in vitamin D supplementation and pre-frail older adults demonstrated a significant and non-significant improvement in sit-to-stand power and SPPB score following an eight week intervention, respectively (19). Discrepancies in SPPB results between our study and the previous research provide further support for the possibility that those with greater deficits may benefit the most from a high dose vitamin D intervention. Our study did not measure power and thus, cannot draw conclusions with the only other measure of lower extremity function from this previous research. However, in consideration with the other findings of our study, these studies synergistically suggest that interventions ≥ 1000 IU/day for 8+ weeks may improve lower extremity function.
Important limitations include the limited sample size that may have affected our ability to find additional significant associations, and the risk of type I error for multiple testing. The open-label design precludes us from ascertaining a significant effect compared with placebo. However, our results provides effect sizes of this intervention that can guide future trials. Given that our stratification reveals that those with greater deficits can benefit from this intervention, we suggest that future studies focus on frail individuals with insufficient vitamin D levels. Ultimately, high dose (4000 IU/day) vitamin D may be a simple and cost-effective intervention to improve and maintain physical performance in older adults with frailty.
Vitamin D supplementation, in a daily high dose (4000 IU) is safe, feasible, and has a beneficial effect on physical performance in older adults with frailty and those with insufficient vitamin D levels. A larger randomized controlled trial is required to confirm our findings.

 

Funding: Canadian Institute of Health Research (MIA – 85856). The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.
Acknowledgements: The authors would like to thank Anam Islam for her assistance in the data collection and preliminary analyses of this study, research pharmacist Leanne Vanderhaeghe who provided the vitamin D blister packages, and Dr. Yanina Sarquis-Adamson for proof reading the final version of the manuscript. Nick Bray is a recipient of a 2018-2019 Ontario Graduate Scholarship (OGS). Dr. Montero-Odasso’s program in Gait and Brain Health is supported by grants from the Canadian Institute of Health Research (MOP 211220; PJT 153100), the Ontario Ministry of Research and Innovation (ER11–08–101), the Ontario Neurodegenerative Diseases Research Initiative (OBI 34739), the Canadian Consortium on Neurodegeneration in Aging (FRN CNA 137794), and Department of Medicine Program of Experimental Medicine Research Award (POEM 768915), University of Western Ontario. He is the first recipient of the Schulich Clinician-Scientist Award.
Conflict of Interest: The authors declare no conflict of interest.

 

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MUSCLE QUALITY, STRENGTH, AND LOWER EXTREMITY PHYSICAL PERFORMANCE IN THE BALTIMORE LONGITUDINAL STUDY OF AGING

 

N. CHILES SHAFFER1, E. FABBRI1,2, L. FERRUCCI1, M. SHARDELL1, E.M. SIMONSICK1, S. STUDENSKI1

 

1. Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21225, USA; 2. Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy.
Corresponding author: Nancy Chiles Shaffer, Ph.D., National Institute on Aging, MedStar Harbor Hospital, 3001 S. Hanover Street, 5th Floor, Baltimore, MD 21225, USA, Office: 410-350-3971, Fax: 410-350-7304, Email: nancy.chiles@nih.gov

J Frailty Aging 2017;in press
Published online August 9, 2017, http://dx.doi.org/10.14283/jfa.2017.24

 


Abstract

Background: Muscle quality is defined as the force generated by each volumetric unit of muscle tissue. No consensus exists on an optimal measure of muscle quality, impeding comparison across studies and implementation in clinical settings. It is unknown whether muscle quality measures that rely on complex and expensive tests, such as isokinetic dynamometry and computerized tomography correlate with lower extremity performance (LEP) any better than measures derived from simpler and less expensive tests, such as grip strength (Grip) and appendicular lean mass (ALM) assessed by DXA. Additionally, whether muscle quality is more strongly associated with LEP than strength has not been fully tested. Objectives: This study compares the concurrent validity of alternative measures of muscle quality and characterizes their relationship with LEP. We also whether muscle quality correlates more strongly with LEP than strength alone. Design: Cross-sectional analysis. Setting: Community. Participants: 365 men and 345 women 65 years of age and older in the Baltimore Longitudinal Study of Aging. Measures: Thigh cross-sectional area (TCSA), isokinetic and isometric knee extension strength (ID), BMI adjusted ALM (ALMBMI) from DXA, and Grip. Concurrent validity was assessed as the percent variance of different measures of LEP explained by each muscle quality measure. In addition, we compared LEP relationships between each measure of strength and its correspondent value of muscle quality. Confidence intervals for differences in percent variance were calculated by bootstrapping. Results: Grip/ALMBMI explained as much variance as ID/TCSA across all LEP measures in women and most in men. Across all LEP measures, strength explained as much variance of LEP as muscle quality. Conclusions: Grip/ALMBMI and ID/TCSA measures had similar correlations with LEP. Muscle quality did not outperform strength. Although evaluating muscle quality may be useful to assess age-related mechanisms of change in muscle strength, measures of strength alone may suffice to understand the relationship between muscle and LEP.

Key words: Muscle Quality, muscle strength, physical performance.


 

 

Introduction

Muscle quality (MQ) can be conceptualized as the capacity to generate force relative to the mass/volume of contractile tissue (1-3). Declines in muscle strength with aging are not explained by declines in muscle mass; the concept of MQ was meant to describe this phenomenon (1, 2, 4-6). While strength alone quantifies the amount of force a muscle can generate, bigger muscles are not necessarily stronger. A smaller muscle may be more effective due to more contractile proteins, less fat infiltration, or other physiological properties that can alter the quality of the muscle (3, 6, 7). Therefore, MQ could be useful to comprehensively quantify physiological changes in skeletal muscle that occur with aging.
MQ has been assessed in multiple studies using different operational definitions (2, 3, 6, 8-14). In general, MQ is defined as the ratio of strength to mass, but it remains unclear which are the optimal methods to assess strength and mass.  Previous studies used the ratio of quadriceps isokinetic peak torque (Quad) via isokinetic dynamometry (ID) to thigh muscle cross-sectional area (TCSA) assessed by computed tomography (CT) to characterize the effect of age and other risk factors on MQ (8, 12, 13, 15). The feasibility of this approach on a large scale is limited because CT and ID are expensive, time consuming to ascertain and difficult to process (10, 16, 17). ID allows for measurement of contractile force at constant velocity; however, it is more expensive than a hand dynamometer (HD) (18) and can be difficult for some older adults to complete due to lower back or leg pain and/or poor strength (13). In addition, whether ID/TCSA better captures the effect of muscle impairment on mobility compared to other measures of MQ is unknown. A simpler and less expensive method to assess MQ compared to ID/TCSA is the ratio of grip strength (Grip) via HD to appendicular lean mass (ALM) assessed via dual-energy X-ray absorptiometry (DXA). HD/DXA ratio has the advantage of requiring inexpensive instruments available in many research and clinical facilities and, therefore, can be easily assessed in most research or clinical situations.
This study aimed to compare the concurrent validity of alternative measures of MQ using lower extremity performance as the reference outcome. Lower extremity performance was used because it is widely considered the gold standard measure to assess the impact of muscle on mobility in older persons.  We additionally tested the hypothesis that measures of MQ correlate with measures of lower extremity performance more strongly than strength.

 

Methods

Baltimore Longitudinal Study of Aging

The Baltimore Longitudinal Study of Aging (BLSA), which began in 1958, is the longest running study in the United States dedicated to studying human aging. Designed to assess normative aging, the BLSA is an observational study that continuously enrolls healthy adults aged 20 years and older. Follow-up study visits occur every 2 years for participants age 60-80, and annually for participants over 80 years of age. All enrolled participants gave informed consent. Further details on the study design have been previously reported (19).

Analytic Sample

This cross-sectional analysis included data from 365 men and 345 women aged 65 to 97 years visited between February 2011 and September 2015. All participants had measures of TCSA, ALM adjusted for body mass index (BMI) (ALMBMI), ID, and Grip.

Measures

Muscle Mass

Two measures of muscle mass were assessed, TCSA and ALM. TCSA was measured from 10mm CT scan of the mid-femur. Images were then filtered using the GEANIE BonAlyse software.  TCSA was normalized for body height by dividing by height squared (TCSAht2). ALM was acquired from DXA whole body scans from the Prodigy Scanner using the Encore Software. ALM (kg) is the sum of the lean mass of the right and left arm and the right and left leg. ALM was normalized by dividing by BMI (ALMBMI).

Muscle Strength

Multiple ID muscle strength measures were acquired from a BioDex dynamometer. First, quadriceps peak torque (Quad)(Nm), an isokinetic strength measurement, was taken as the maximum of five trials of concentric knee extension strength at an angular velocity of 30°/s and 180°/s. Additionally, hamstring peak torque (Ham)(Nm) was taken as the maximum of five trials of concentric knee flexion strength at an angular velocity of 30°/s and 180°/s. Finally, isometric knee extension (Nm) was taken as the maximum of five trials at 120° and 140°. Grip was measured via a Jamar Hydraulic hand dynamometer, which registers maximum kg of force from three trials on each hand. The average of each trial was used for this analysis, consistent with previous studies(20).

Muscle Quality

In general, MQ was assessed as a ratio between a measure of strength and a measure of muscle mass in different combinations. The difficult and expensive MQ measures are each of the ID strength measures divided by TCSAht2. The easy and relatively inexpensive MQ measure was Grip divided by ALMBMI.

Lower Extremity Physical Performance

Usual gait speed and rapid gait speed were each assessed on a 6m walking course. Participants were advised to walk at their usual pace or as fast as possible, respectively. The average gait speed is the average of two trials of participants walking at a usual pace, while rapid gait speed is the maximum of two trials where participants walked at their fastest pace.  400m walk time is derived from an endurance test, done as quickly as possible, conducted in an unobstructed corridor over a 20m long walking course.
The Short Physical Performance Battery (SPPB), an objective measure of lower-extremity function, comprises 4m usual gait speed, three standing balance tests, and time to complete five chair rises (Guralnik et al., 2000). Each of the three components of the SPPB are scored on a 0 to 4 scale, resulting in an overall SPPB score ranging from 0 to 12, with 12 indicating highest performance. The Health ABC Physical Performance Battery (HABCPPB) (Simonsick et al., 2001) is an extension of the SPPB aimed at avoiding a ceiling effect in a relatively high functioning population, including maintaining balance for longer time, a single leg stand and a narrow walk. Each component of the HABCPPB is scored on a continuous ratio scale ranging from 0 to 1, resulting in an overall HABCPPB score of 0 to 4, with 4 indicating highest performance.
Participants able to rise from a chair without assistance from chair arms completed repeated chair stands. Each chair stand pace is the ratio of number of chair stands completed to time (5s).

Analytic Strategy

Generalized linear models were used to predict average gait speed, rapid gait speed, 400m walk speed, SPPB, HABCPPB,  and 5s chair stand pace. All analyses were stratified by sex and each model was adjusted for age. Concurrent validity was assessed as the percent variance (R2) of the physical performance measures explained by each MQ measure. In addition, the amount of variance explained in each mobility outcome by different MQ measures were compared with their respective strength measure.
Bootstrapping was performed to compute confidence intervals for differences in percent variance explained by different models. The methods used for bootstrapping in SAS have been previously reported(21). A random seed was used for unrestricted random sampling of equal size as the original dataset. One thousand bootstrap samples were generated. From the bootstrap samples, generalized linear models were run with each physical performance measure as the dependent variable, and age and the MQ measures as the independent variables. The differences in R2 values from each of the ID MQ variables and Grip/ALMBMI were calculated. The bootstrap samples were used to generate a 95% confidence interval for the differences in R2 values. The same bootstrapping method was used to compare the difference in R2 values from each of the MQ measures and its respective strength variable.

 

Results

Characteristics of the study sample are shown in Table 1. The average ages were 78.0 and 76.2 years for men and women, respectively. On average, participants tended to be slightly overweight and highly functional for their age (22).

 

Table 1 Sample Characteristics

Table 1
Sample Characteristics

*SPPB=Short Physical Performance Battery, Health ABC PPB=The Health, Aging, and Body Composition Study Physical Performance Battery.

 

Forest plots depicting the difference in R2 values of each comparison difficult and expensive MQ measure to Grip/ALMBMI, and the respective 95% confidence intervals are shown in Figures 1 for women and men. The vertical line at the center of each plot, zero, represents no significant difference between the percent variance of a comparison MQ measure and Grip/ALMBMI. For each horizontal line, the center symbol is the difference in R2 values (R2 of respective MQ measure minus R2 Grip/ALMBMI), and the lines are the 95% confidence interval. The numerical values for percent variance in physical performance explained by each MQ measure is shown in Supplemental Table 1 for men and women separately. In women, Grip/ALMBMI and all ID/TCSA MQ measures explained comparable percent variances of the different physical performance outcomes. In men, in most instances, Grip/ALMBMI explained as much percent variance as ID/TCSA MQ measures for different performance outcomes. Exceptions were Quad180/TCSAht2, and Ham180/TCSAht2 that explained a higher percent variance in average gait speed and Quad180/TCSAht2 that explained a higher percent variance in rapid gait speed.
Figure 2 shows forest plots depicting the differences in R2 values of each MQ measure to its respective strength measure (R2 MQ minus R2 strength), and the 95% confidence intervals for the differences. The construct of these forest plots is the same as previously described for Figure 1. The numerical percent variances of MQ versus strength for women and men are displayed in Supplemental Table 2. In women, there was no instance where MQ explained more variance than strength alone. Additionally, models fitted with MQ or strength measures yielded similar fit in term of R-square. In men, there were also no occasions where MQ produced a percent variance greater than strength alone. Strength alone, however, did produce significantly higher percent variance values compared to MQ in a few models: Ham180 when modeling rapid gait speed; Quad180, Ham30, and Ham180 when modeling rapid gait speed, and Quad180 when modeling chair stand 5s pace.

 

Figure 1 Difference in R2 in Muscle Quality Measures Compared to Grip/(ALM/BMI) in Women and Men

Figure 1
Difference in R2 in Muscle Quality Measures Compared to Grip/(ALM/BMI) in Women and Men

Quad30=quadricep peak torque at 30°/s, MQ=muscle quality, Quad180=quadricep peak torque at 180°/s, Ham30=hamstring peak torque at 30°/s, Ham180=hamstring peak torque at 180°/s, Isomet120=isometric knee extension at 120°/s, Isomet140=isometric knee extension at 140°/s. *All MQ measures are adjusted for Thigh cross-sectional area (kg) divided by height squared (m2). † Difference in R2 = Comparison MQ R2 – Grip/ALMBMI R2.

Figure 2 Difference in R2 in Muscle Quality Measures Compared to Strength in Women and Men

Figure 2
Difference in R2 in Muscle Quality Measures Compared to Strength in Women and Men

Grip=grip strength, MQ=muscle quality, Quad30=quadricep peak torque at 30°/s, Quad180=quadricep peak torque at 180°/s, Ham30=hamstring peak torque at 30°/s, Ham180=hamstring peak torque at 180°/s, Isomet120=isometric knee extension at 120°/s, Isomet140=isometric knee extension at 140°/s. *Grip MQ is adjusted for appendicular lean mass (kg) divided by BMI (kg/m2). All other MQ measures are adjusted for Thigh cross-sectional area (kg) divided by height squared (m2). † Difference in R2 = MQ R2 – Strength R2.

 

Discussion

For most of the physical performance outcomes, measures of MQ based on expensive, time consuming and not widely available tests, such as CT and lower extremity dynamometry were not better correlates of measures of mobility or lower extremity performance than measures of MQ based on handgrip strength and a DEXA derived measure of lean body mass. Exceptions, found only in men, were Quad180/TCSAht2 with average gait speed and rapid gait speed, and Ham30/TCSAht2 with average gait speed. Overall, ID/CT MQ measures comparably correlated with several physical performance measures as Grip/ALMBMI, including higher order, more sensitive performance measures. Additional measures of MQ were explored in this study, specifically ID/DXA, Isometric/CT, and HD/CT measures, however none performed as well as ID/CT or HD/DXA (data not shown). MQ measures of Grip with DXA acquired upper extremity lean mass and lower extremity lean mass were also assessed but produced R2 values equivalent to Grip/ALMBMI, therefore they were not reported. These results suggest that Grip/ALMBMI is a valid if not superior substitute for more costly and burdensome measures of MQ.

To our knowledge, this is the only study to compare multiple measures of MQ as correlated with multiple physical performance measures. A previous comparison of grip strength, knee extension strength, and lower extremity muscle power found no statistical difference between measures in ability to identify those with gait speed less than 0.8 m/s (11).
When comparing MQ to muscle strength, all muscle strength measures explained as much, if not more, variance than their respective MQ measures. When assessing physical function, strength alone may be the appropriate measure of muscular function. Other studies have also reported stronger associations between muscle strength vs MQ and physical performance measures. A comparison of multiple measures of CT acquired body composition and ID acquired muscle strength in the Age, Gene/Environment Susceptibility-Reykjavik (AGES-Reykjavik) Study found muscle strength to have the strongest associations with decline in gait speed over 5 years in men and women when compared to muscle mass, MQ, muscle attenuation, and intermuscular adipose tissue (14). Similarly, a comparison of muscle mass, muscle strength, and MQ in older men found muscle strength to have the strongest magnitude of association with functional limitation and physical disability and thus was the best clinical indicator of age-related muscle change(9). The current findings add to these previous studies by additionally assessing a MQ measure with muscle mass from CT and isokinetic quadricep strength. These results suggest that strength may suffice as a measure of muscle in a clinical setting.
A review assessing the optimal MQ measure suggested that muscle power, or the rate at which force is developed, should be used with muscle mass and muscle strength(1). They also concluded that energetic metabolism may add insight into the mechanisms that support MQ(1). It is possible that these additions may produce a MQ measure that correlates with physical performance better than strength alone.
MQ may provide a differential diagnosis of poor physical performance. Poor physical performance in the presence of normal MQ may be due to issues such as arthritis and pain, whereas poor physical performance with deficient MQ may be due to fat infiltration, decreased innervation, or decreased metabolism. Additionally, there are several factors that impact physical performance beyond strength and MQ, as evidenced by the modest R2 values obtained in these analyses.
The BLSA allowed for the comparison of multiple MQ measures, including HD/DXA and ID/CT with respect to their association with several different physical performance outcomes of varying difficulty. A limitation of the BLSA is that it comprises a population that is healthy upon enrollment, therefore the results may not be generalizable to the broader older adult population. However, given that the muscular and physical function of many of the BLSA participants may be higher than that of the overall older adult population, it is possible that these results would be stronger in the general population. Even with the health of the BLSA population, 29% of those 65 and older who completed the handgrip assessment did not complete the BioDex, primarily due to pain or safety concerns. This proportion would probably be greater in the general population, highlighting the need for an easy and inexpensive clinical assessment of muscle for older adults of varying health statuses. An additional limitation is the lack of assessment of adiposity, particularly intramuscular fat, on MQ. Adiposity is associated with poorer MQ (14, 23); therefore, future research should assess whether the impact of adiposity on MQ differs by MQ measure.
From these results, it appears that Grip/ALMBMI is as good a MQ measure as those obtained using much more expensive and labor intensive machinery, such as Quad30/TCSAht2. Further assessment will be needed to determine if these finding are maintained longitudinally. Grip/ALMBMI may not be as sensitive to detecting change in physical performance; however, it could serve as an easily obtained initial screening tool for clinical application to identify older adults in need of more precise/extensive assessment of MQ. Furthermore, strength measures alone appear sufficient for assessing muscle function as it relates to physical performance.

 

Funding: This research was supported by the Intramural Research Program of the National Institutes of Health, National Institute on Aging.
Conflict of interest: None

 

References

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3.    Fragala, MS, Dam TT, Barber V, et al. Strength and function response to clinical interventions of older women categorized by weakness and low lean mass using classifications from the Foundation for the National Institute of Health sarcopenia project. J Gerontol A Biol Sci Med Sci 2015;70(2):202-9.
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6.    Newman AB, Haggerty CL, Goodpaster B, et al. Strength and muscle quality in a well-functioning cohort of older adults: the Health, Aging and Body Composition Study. J Am Geriatr Soc 2003;51(3):323-30.
7.    Lexell J, Taylor CC, Sjostrom M. What is the cause of the ageing atrophy? Total number, size and proportion of different fiber types studied in whole vastus lateralis muscle from 15- to 83-year-old men. J Neurol Sci 1988;84(2-3):275-94.
8.    Goodpaster BH, Park SW, Harris TB, et al. The loss of skeletal muscle strength, mass, and quality in older adults: the health, aging and body composition study. J Gerontol A Biol Sci Med Sci 2006;61(10):1059-64.
9.    Hairi NN, Cumming RG, Naganathan V, et al. Loss of muscle strength, mass (sarcopenia), and quality (specific force) and its relationship with functional limitation and physical disability: the Concord Health and Ageing in Men Project. J Am Geriatr Soc 2010;58(11):2055-62.
10.    Heymsfield SB, Gonzalez MC, Lu J, et al. Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia. Proc Nutr Soc 2015;74(4):355-66.
11.    Lauretani F, Russo CR, Bandinelli S, et al. Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol 2003;95(5):1851-60.
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14.    Reinders I, Murphy RA, Koster A, et al. Muscle Quality and Muscle Fat Infiltration in Relation to Incident Mobility Disability and Gait Speed Decline: the Age, Gene/Environment Susceptibility-Reykjavik Study. J Gerontol A Biol Sci Med Sci 2015;70(8):1030-6.
15.    Overend TJ, Cunningham DA, Kramer JF, et al. Knee extensor and knee flexor strength: cross-sectional area ratios in young and elderly men. J Gerontol, 1992;47(6):M204-10.
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22.    Simonsick EM, Schrack JA, Glynn NW, et al. Assessing fatigability in mobility-intact older adults. J Am Geriatr Soc 2014;62(2):347-51.
23.    Koster A, Ding J, Stenholm S, et al. Does the amount of fat mass predict age-related loss of lean mass, muscle strength, and muscle quality in older adults? J Gerontol A Biol Sci Med Sci 2011;66(8):888-95.

PREVALENCE OF SARCOPENIA IN COMMUNITY-DWELLING CHILEAN ELDERS ACCORDING TO AN ADAPTED VERSION OF THE EUROPEAN WORKING GROUP ON SARCOPENIA IN OLDER PEOPLE (EWGSOP) CRITERIA

 

L. LERA1, C. ALBALA1, H. SÁNCHEZ1, B. ANGEL1, M.J. HORMAZABAL1, C. MÁRQUEZ1, P. ARROYO2

 

1. Institute of Nutrition and Food Technology (INTA) – University of Chile, Santiago, Chile; 2. Radiology Department, Clinical Hospital, University of Chile, Independencia, Santiago, Chile.
Corresponding author: Dr. Cecilia Albala, Public Health Nutrition Unit, Institute of Nutrition and Food Technology (INTA) – University of Chile, El Líbano 5524, Casilla 138-11, Santiago, Chile, E-mail: calbala@uchile.cl

J Frailty Aging 2017;in press
Published online November 30, 2016, http://dx.doi.org/10.14283/jfa.2016.117

 


Abstract

Abstract: Background: Sarcopenia is the progressive loss of mass and skeletal muscle strength and has serious consequences on older people’s health. The Chilean older population has a high life-expectancy, but the prevalence of functional dependence is also high. Objective: To determine the prevalence of sarcopenia in Chilean older adults and its relationship with age, gender, and body mass index (BMI). Design: Cross-sectional study. Setting: Community. Participants: 1,006 non-disabled, community-dwelling subjects aged 60 years or older living in Santiago. Measurements: Anthropometric measurements, handgrip strength, physical performance tests, and dual-energy-x-ray-absorptiometry (DXA) scan were performed. Sarcopenia was defined using the algorithm of the European Working Group on Sarcopenia in Older People (EWGSOP). Muscle mass was measured with DXA scan; skeletal muscle mass index (SMI) and hand dynamometry were defined with cut-off points obtained for the Chilean population. For a 3m walking speed we used the cut-off point of the EWGSOP definition. Nutritional status and obesity were defined according to World Health Organization standards. Association between sarcopenia and age, gender, BMI and lean/fat mass ratio was estimated by logistic regression models. Results: The prevalence of sarcopenia was 19.1% (95%CI: 16.8%-21.8%), similar in men and women. There was an increasing trend of sarcopenia by age group and a decreasing trend with nutritional status. After logistic regression, sarcopenia was positively associated with age (OR=1.10; 95%CI:1.06-1.15) and falls (OR=1.83; 95%CI:1.07-3.15) and negatively associated with overweight (OR=0.31; 95%CI:0.16-0.59), obesity (OR=0.02; 95%CI:0.004-0.11), lean mass/fat mass ratio (OR=0.69; 95%CI:0.48-0.9997), knee height (OR=0.78; 95%CI:0.68-0.89) and calf circumference (OR=0.87; 95%CI:0.77-0.97). Conclusions: The total prevalence of sarcopenia was 19.1% increasing with age reaching 39.6% in people of 80 or more years of age. A negative association of sarcopenia with overweight, obesity and lean/fat mass ratio was observed. Although the high prevalence of obesity (35.9%), only 2% of obese people were sarcopenic.

Key words: Sarcopenia, muscle mass, muscle strength, community-dwelling older people.


 

 

Introduction

Sarcopenia is a characteristic of biological ageing that involves a progressive loss of mass and skeletal muscle strength and has a serious impact on the health of older people (1–3). Considering that sarcopenia is mainly an age-associated syndrome, in fast aging countries with large socioeconomic inequalities such as Latin American countries, the adverse consequences of this syndrome can be immense. Chile has a life expectancy at birth comparable to the developed world, reaching 82.2 for women and 78.5 for men in the period 2010–2015. However, the prevalence of functional dependence is also high, mainly in people of low socioeconomic status (4).
The prevalence of sarcopenia varies according to age group and the criteria used. The wide variation reported ranged from 13.5% to 25% in people under 70 years and from 25% to 60% in people over 80 years of age (5,6) and is probably due to a lack of specific cut-off points for population from different ethnic backgrounds and the different techniques used for assessing muscle mass. Muscle mass can be measured with a dual-energy x-ray absorptiometry (DXA) scan, magnetic resonance imaging or Bioimpedance analysis (1). A DXA scan is the most commonly used as gold standard (7).
In 2010, the European Working Group on Sarcopenia in Older People (EWGSOP) developed a practical clinical definition and consensus diagnostic criteria by means of a diagnostic algorithm. The EWGSOP defines sarcopenia as “a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength with a risk of adverse outcomes such as physical disability, poor quality of life and death” (1).
The diagnostic algorithm is based on a screening in series where muscle function (physical performance and strength muscle) is evaluated first. If the subject has low muscle function, then it is necessary to evaluate body composition, in particular appendicular skeletal muscle mass (ASM) (1). Using the definition of the EWGSOP, the recently published review (6) reported a prevalence of sarcopenia varying between 1% and 30%. Considering that the racial, ethnic composition, and morphological characteristics of the Latin American population differs from the European (8), we used cut-off points of muscle mass measured by DXA scan and muscle strength obtained in a large Chilean population (9). The objective of this study was to calculate the prevalence of sarcopenia and its associated factors in Chilean older people using the algorithm of the EWGSOP.

 

Methods

Cross-sectional study in 1,006 (68.3% female) community-dwelling, non-disabled subjects ≥60 years living in Santiago and participating in ALEXANDROS and ISAmayor studies (4,10).
After signing an informed consent approved by the ethics committee of the Institute of Nutrition and Food Technology, all subjects underwent face-to-face interviews including self-reported chronic diseases (hypertension, diabetes, cancer, COPD, stroke), self-reported functional limitations, and self-perceived symptoms of depression measured by the Short Form of the Geriatric Depression Scale (GDS-15).
A DXA scan was performed in the whole sample in order to assess body composition. Handgrip strength was measured by means of handgrip dynamometry (Hand Dynamometer T-18, Country Technology, Inc.), registering the best of two measurements with the dominant hand. Three meters walking speed was registered. Anthropometric measurements of weight, height, and knee height; as well as waist, hip, calf, and arm circumferences were done according to methods described previously (10). Their Appendicular skeletal muscle mass index (SMI) was calculated as the ratio of ASM and height2 (kg/m2). Low muscle mass was defined using the 20th percentile (p20) of SMI calculated on a sample of 565 subjects (9). Nutritional status and obesity were defined according to World Health Organization (WHO) standards. Sarcopenia was defined using the consensus criteria and the algorithm of the EWGSOP (1). Low SMI was defined with cut-off points obtained for the Chilean population (men: 0.8 m/sec).

Stages of sarcopenia —pre-sarcopenia, sarcopenia, and severe sarcopenia— were also determined by the suggested classification of the EWGSOP (1). These are characterized by low muscle mass (pre-sarcopenia), low muscle mass and low muscle strength or low physical performance (sarcopenia) and low muscle mass, low muscle strength and low physical performance (severe sarcopenia).

Statistical analysis

Continuous variables were expressed as mean ± Standard Deviation (SD) and 95% confidence intervals (95%CI). Categorical variables were expressed as median or percentages and 95%CI. The difference between genders was calculated by a two-sample mean-comparison test or Pearson’s Chi2 test, depending on the kind of variable. Differences among age groups and levels of sarcopenia were estimated by Pearson‘s Chi2 test and by a test for trend across ordered groups. Logistic regression models were performed to analyze the association between studied variables (risk factors, age, anthropometric measurements), adjusted by sex and the presence or absence of sarcopenia. The Hosmer–Lemeshow test was used to assess the goodness of fit for the estimated models. The ratio of lean mass to fat mass was calculated to adjust the relationship between BMI and sarcopenia.
All statistical analyses were performed using STATA 14 (StataCorp.2015. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP).

 

Results

Table 1 shows the socio-demographic, health characteristics, anthropometric variables, body composition, handgrip strength, and physical performance tests of the study sample by sex. Men represented 31.7% of the total sample. The mean age was similar for men and women (67.7±5.7 and 67.6±6.0 years; respectively).  There were no differences between age groups by gender. Less than 11% of the older adults lived alone: 8.8% of the men and 10.2% of the women lived alone (non-significant). The mean years of education were similar in men and women (7.5 and 7.7 years; respectively), and the distribution of the different levels was also similar by sex. The frequency of one or more disabilities on the Activities of Daily Living (ADL) was similar in men and women (4.7% vs 3.9%; respectively), and the percentage of one or more disabilities on the Instrumental Activities of Daily Living (IADL) was significantly higher in men than women (17.6% vs 12.9%). Diabetes and symptoms of depression were similar in men and women. The percentage of men with zero diseases was significantly higher than the women’s (39.4% vs 31.6%; respectively). Men smoked significantly more than women (19.1% vs 13.1%; respectively). The number of falls and fractures were significantly higher in women than men (Falls: 37.8% vs 22.9%; Fractures: 18.9% vs 12.9%; respectively). The BMI was higher in women than men (29.2 kg/m2 vs 27.8
kg/m2; respectively), and consequently the prevalence of obesity (39.8% vs 27.7%; respectively). Lower handgrip strength (18.7 kg vs 32.8 kg), ASM (14.4  kg vs 21 kg), SMI (6.3 kg vs 7.7 kg), lean mass (35.8 kg vs 49.7 kg) and lean mass/fat mass ratio (1.4 vs 2.5) were found to be lower in women than in men. Fat mass was higher in women than men (28.5 kg vs 23.7 kg; respectively). With regard to the physical performance test (3 meters walking speed), men had higher values than women (0.89 m/s vs 0.80 m/s; respectively), with 68.2% of the men and 49.2% of women achieving a speed >0.8 m/sec.

Table 1 Socio-demographic, health characteristics and physical performance of the study sample by sex

Table 1
Socio-demographic, health characteristics and physical performance of the study sample by sex

Results are presented as mean ± SD, or percentage (n);GDS: Geriatric depression scale; ADL: Activities of Daily Living; IADL: Instrumental ADL; BMI: Body Mass Index: ASM: Appendicular Skeletal Muscle: SMI: Skeletal Muscle Index; * p<0.05; † p<0.0001

 

The prevalence of sarcopenia by age group (60-64.9; 65-69.9; 70-74.9; 75-79.9 and ≥80 years), gender, and whole sample is shown in Figure 1. The prevalence increases significantly with increasing age groups in the total sample and by gender. The prevalence of sarcopenia in the total sample is similar in men and women (19.4% vs 18.9%; respectively).

 

Figure 1 Prevalence of sarcopenia by age and gender

Figure 1
Prevalence of sarcopenia by age and gender

 

The prevalence and the prevalence ratio of sarcopenia by nutritional status and gender are presented in Table 2. There is a decreasing trend of sarcopenia with nutritional status in both genders (men: 71.4; 41.8; 15.3; 2.3% and women: 76.9; 46.8; 19; 1.9%), showing only 2% of the obese being sarcopenic. We observed a dose-response relationship in relation to nutritional status; older people with low weight (BMI<20 kg/m2) are 1.7 times more likely to be sarcopenic than people presenting a normal weight, whereas overweight and obese adults (BMI≥25 kg/m2) are less likely to be sarcopenic compared to subjects of normal weight for the entire sample and by gender. Overweight and obese subjects had higher lean mass and grip strength than underweight and normal subjects (see supplementary table).

 

Table 2 Prevalence and prevalence ratio of sarcopenia by nutritional status and gender

Table 2
Prevalence and prevalence ratio of sarcopenia by nutritional status and gender

Reference: Normal weight; CI: confidence interval; PR: Prevalence Ratio; p<0.0001 (Sarcopenia vs Nutritional status by gender)

 

Table 3 shows the classification of stages of sarcopenia by gender. Pre-sarcopenia was identified in 6.5% of the total sample and severe sarcopenia in 2.2% of the sample. No differences between men and women were observed.
Three logistic regression models for the association of sarcopenia with anthropometric variables, lean/fat mass ratio, diabetes and falls adjusted by age and sex are displayed in Table 4. In an age, sex and lean/fat mass ratio adjusted model, compared with those with normal nutritional state, overweight (OR=0.21; 95%CI: 0.13-0.30) and obesity (OR=0.017; 95%CI: 0.008-0.04) were independently associated with lower risk of sarcopenia. On the other hand underweight was associated with higher risk of sarcopenia (OR=9.10; 95%CI: 2.16-38.32). After additional adjustment by knee height, calf circumference, diabetes and falls the negative association of obesity (OR=0.31; 95%CI: 0.16-0.59) and overweight (OR=0.02; 95%CI: 0.004-0.11) remained significant. On the other hand, a positive association of sarcopenia with falls was observed (OR=1.83; 95%CI:1.07-3.15).

 

Table 3 Classification by stages of sarcopenia and gender

Table 3
Classification by stages of sarcopenia and gender

Pearson‘s Chi2 test: Sarcopenia levels vs gender: p>0.1

Table 4 Logistic regression models of the risk factors associated with sarcopenia, adjusted by sex and age

Table 4
Logistic regression models of the risk factors associated with sarcopenia, adjusted by sex and age

OR: odds ratio; CI: confidence interval; Reference category of dependent variable: Non-sarcopenia; * Normal nutritional state is used as reference group; Hosmer-Lemeshow’s goodness-of-fit test: † Chi2(8) =9.75; p=0.28; ‡ Chi2(8) =3.64; p=0.89; § Chi2(8) =7.06; p=0.53

 

 

Discussion

In this study, we report the prevalence of sarcopenia in a sample of 1,006 older adults Chileans using the consensus definition developed by the EWGSOP (1), which was previously validated by our group (9). We found a prevalence of sarcopenia of 19.1%, similar for men and women. The prevalence of sarcopenia increased with age from 12.3% in the 60–64 y group to 38.5% in subjects ≥80 years. A wide range of sarcopenia prevalence (4.1 to 24.2) has been reported in Europe, Asia, and the USA with the same diagnostic criteria (1)  (1, 6, 7, 12–15). In Asian countries, the figures vary in different studies. The study of Yamada in community-dwelling Japanese people aged 65 to 89 found a slightly higher prevalence of sarcopenia than ours: 21.8% in men and 22.1% in women (16). However, Sanada, using two reference cut-off points for SMI from Japanese people, found a prevalence between 6.7% and 56.7% in men and 6.3% and 33.6% in women aging 70-85 years, depending on the reference values of SMI used (17).
In Taiwan, Wu et al. (18) studied the prevalence of sarcopenia and associated factors with severe sarcopenia in 549 older adults living in communities situated in both urban and rural zones using the consensus definition developed by the EWGSOP. They found that only 12.7% of the subjects had sarcopenia. However, it is important to highlight that differences may be due to different cut-off points or methods used, even though the same diagnostic criteria was employed. Recently, in a Belgian study (19) conducted in 400 people ≥65 years of age, the prevalence of sarcopenia varied between 9.25% and 18% depending on the different cut-offs and criteria used for diagnosing sarcopenia.
On the other hand, in Taiwan (20) the prevalence of sarcopenia was found to vary between 5.8% to 14.9% in men and 4.1% to 16.6% in women, depending on the International Working Group on Sarcopenia or the EWGSOP criteria used.
Studies are scarce in Latin America. To our knowledge, this is the first study in Latin America calculating the prevalence of sarcopenia using a DXA scan to measure ASM. A study of prevalence done in Mexico City estimated the prevalence of sarcopenia in 25.6%, in the group of 60 to 79 years of age and 50.4% in subjects ≥80 years of age. In that study, lower muscle mass was estimated using a calf circumference lower than 31 cm (21), a good clinical indicator of disability and physical function, but not as DXA for screening of sarcopenia (2). A similar study, using calf circumference, estimated prevalence of sarcopenia (11.5%) and frailty (9.4%) in Colombia (22). In a Brazilian study, muscle mass was estimated through the Lee prediction equation. They found a prevalence of sarcopenia of 16.1% in women and 14.4% in men from the SABE study (23) using the EWGSOP diagnostic algorithm.
In relation to the different stages of sarcopenia, only 2.2% of the sample in the current study had severe sarcopenia. We found only one study reporting severe sarcopenia using the EWGSOP definition in the Hertfordshire Cohort Study (24) with results similar to ours (men 1.9%; women 2%). The published prevalence of severe sarcopenia are based on different definitions and methods to assess muscle mass. Janssen, in the Third National Health and Nutrition Examination Survey using Bioelectrical Impedance, found prevalence ranging from 7 to 10% depending on age, with the definition of being under 2SD of young adults’ SMI. Similar results with the same methods were found in some Asian studies (25).
With respect to factors associated with sarcopenia, our main finding is the negative association with BMI (18), with only 2% of the obese being sarcopenic. Moreover, a dose-response was observed in the prevalence of sarcopenia according to nutritional status, showing a negative gradient from underweight to obesity. The prevalence of obesity in the studied group was high (35.9%), although the obesity defined by a BMI≥30kg/m2 was mainly non-sarcopenic. However, in older people, the single use of BMI as a proxy for body composition can be misleading as the same BMI can correspond to different proportions of fat mass and lean mass. To avoid biased interpretations of the former association, we performed a multivariable analysis adjusting by the ratio of lean to fat mass and knee height, a measure that is more representative of the skeleton size in older people (26,27) than the current height. After adjusting, the association remains invariable, meaning that in these cohorts, obese people are not sarcopenic. Obesity has been consistently associated with longer survival (28) and mild obesity in older people has shown a paradoxical association with lower morbidity and better evolution of some chronic diseases such as heart failure and osteoporosis (29). However, the huge lifestyle changes of the Chilean population that have occurred in the past three decades, with high prevalence of obesity and sedentary behaviour  in all groups of age, will lead to a future aged population more  vulnerable to sarcopenic obesity. Other studies in younger cohorts are needed to assess the effect of demographic origin on that characteristic.
Like Morley (13), we also found a strong association between sarcopenia and falls within the past year.
The main limitation of the study is that the cross-sectional design does not allow us to provide evidence about risk factors or consequences of sarcopenia. This issue will be addressed with the follow-up of the subjects involved in the study. Among the strengths of this study, the most important one is that the prevalence of sarcopenia was estimated in a large sample of people based on DXA scan measurements. This type of measurement  is one of the most recommended imaging techniques considering its accuracy, reproducibility and sensitivity (30), although its accessibility in countries with low or medium low economies is scarce. In addition, we used cut-off points of SMI and muscle strength obtained for the Chilean population (9). This will allow us to make international comparisons with similar techniques.
Since sarcopenia is an important cause of multiple negative health outcomes in older people, knowing its actual magnitude is crucial for developing policies and programs for its prevention and control.

 

Funding: This project was supported by FONIS SA12I2337 (Fondo Nacional de Investigación y Desarrollo en Salud) and FONDECYT 1130947 (Fondo Nacional de Desarrollo Científico y Tecnológico).
Conflict of interest: None

 

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Supplementary table: Body composition by sex and nutritional state1

Supplementary table: Body composition by sex and nutritional state1

 

1Test for trend across ordered groups: *p<0.02; **p<0.0001

EFFECTS OF CALORIC RESTRICTION WITH OR WITHOUT RESISTANCE TRAINING IN DYNAPENIC-OVERWEIGHT AND OBESE MENOPAUSAL WOMEN: A MONET STUDY

 

E. NORMANDIN1,2, M. SÉNÉCHAL3,4, D. PRUD’HOMME5,6, R. RABASA-LHORET7,8, M. BROCHU1,2

 

1. Faculty of Physical Activity Sciences, University of Sherbrooke, Sherbrooke, Quebec, Canada; 2. Research Centre on Aging, Institute of Geriatrics of Sherbrooke, Sherbrooke University, Sherbrooke, Quebec, Canada; 3. The Manitoba Institute of Child Health, University of Manitoba, Manitoba, Canada; 4. Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada; 5. Institut de Recherche de l’Hopital Monfort, Ottawa, Ontario, Canada; 6. School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada; 7. Department of Nutrition, Université de Montréal, Montreal, Quebec, Canada; 8. Institut de Recherches Cliniques de Montréal (IRCM), Montreal,
Quebec, Canada.

Corresponding author: Martin Brochu, Ph.D., Research Centre on Aging,1036 Belvédère Sud, Sherbrooke, Québec, Canada, J1H 4C4, Tel. (819) 780-2220 # 45326, Fax. (819) 829-7141, E-mail. martin.brochu@usherbrooke.ca

J Frailty Aging 2015;4(3):155-162
Published online November 10, 2015, http://dx.doi.org/10.14283/jfa.2015.54

 


Abstract

Objective: The dynapenic (DYN)-obese phenotype is associated with an impaired metabolic profile. However, there is a lack of evidences regarding the effect of lifestyle interventions on the metabolic profile of individual with dynapenic phenotype. The objective was to investigate the impact of caloric restriction (CR) with or without resistance training (RT) on body composition, metabolic profile and muscle strength in DYN and non-dynapenic (NDYN) overweight and obese menopausal women. Design: 109 obese menopausal women (age 57.9 ± 9.0 yrs; BMI 32.1 ± 4.6 kg/m2) were randomized to a 6-month CR intervention with or without a RT program. Participants were categorized as DYN or NDYN based on the lowest tertile of relative muscle strength in our cohort (< 4.86 kg/BMI). Measurements: Body composition was measured by DXA, body fat distribution by CT scan, glucose homeostasis at fasting state and during an euglycemic-hyperinsulinemic clamp, fasting lipids, resting blood pressure, fasting inflammation markers and maximal muscle strength. Results: No difference was observed between groups at baseline for body composition and the metabolic profile. Overall, a treatment effect was observed for all variables of body composition and some variables of the metabolic profile (fasting insulin, glucose disposal, triglyceride levels, triglycerides/HDL-Chol ratio and resting diastolic blood pressure) (P between 0.05 and 0.001). No Group X Treatment interaction was observed for variables of body composition and the metabolic profile. However, an interaction was observed for muscle strength; which significantly improved more in the CR+RT NDYN group (all P ≤ 0.05). Conclusions: In the present study, dynapenia was not associated with a worse metabolic profile at baseline in overweight and obese menopausal women. DYN and NDYN menopausal women showed similar cardiometabolic benefit from CR or CR+RT interventions. However, our results showed that the addition of RT to CR was more effective in improving maximal strength in DYN and NDYN obese menopausal women.

 

Key words: Dynapenia, muscle strength, obesity, caloric restriction, resistance training.


 

Introduction

The rapid increase in obesity prevalence has been reported in individuals aged between 55 and 75 years; and particularly in menopausal women (1). The transition to menopause is often accompanied by increased central adiposity, a more atherogenic lipid profile, alterations in glucose metabolism and a sharp rise in type 2 diabetes and cardiovascular disease risk (2, 3). In addition, the consequences of a deteriorated cardiometabolic profile seem to be amplified in older individuals. It is possibly explained by physiologic changes associated with the aging process and/or the concurrence of chronic conditions more frequently observed during this period of life (4). Hence, fat mass increases and muscle mass and strength decrease with the aging process (5). Dynapenia, which refers to the normal age-related loss of muscle strength and power that usually occurs as part of aging, is now recognized as a debilitating and life threatening condition in older persons (6). Dynapenia has been negatively related to functional capacity, metabolic profile (7,8) and mortality (9). The combination of high fat mass accumulations and low muscle strength, phenotype called ‘dynapenic-obesity’ (10), is increasingly prevalent among older individuals (11). Interestingly, this phenotype has been associated with worse metabolic abnormalities compared to both conditions alone (11).

The few studies that have investigated the effects of DYN-obese phenotype in older individuals mostly looked at functional capacity (10) disability and mortality (11). A recent cross-sectional study has quantify the independent and additive effects of dynapenia and abdominal obesity on the metabolic syndrome in older men and women (12). Results showed that DYN-obese individuals have more metabolic alterations than those displaying dynapenia alone or those with neither abdominal obesity nor dynapenia. Furthermore, to our knowledge, only one study has examined the effect of a lifestyle intervention in DYN-obese individuals on the metabolic profile (13). Results of this study suggest that caloric restriction (CR) with or without resistance training (RT) is effective in improving the metabolic profile [total cholesterol (chol), low-density lipoprotein cholesterol (LDL-chol), systolic and diastolic blood pressure] in DYN-obese menopausal women. However, the study has some limitations such as a limited number of participants in each group, and no measures of visceral fat (VF) and insulin sensitivity. Also, because of the study design, they did not compare subjects displaying DYN- and non-dynapenic (NDYN-) obesity phenotypes. Consequently, the comparison of the effect of a weight loss intervention on DYN and NDYN obese individuals needs to be further investigated.

Thus, the current study’s objective was to compare the effect of CR alone or in combination with RT on body composition, the metabolic profile and muscle strength in DYN and NDYN overweight and obese menopausal women. We hypothesized that interventions aimed to increase muscle strength and decrease obesity levels would have greater effects on the metabolic profile and muscle strength in DYN overweight and obese women.

Methods

Subjects

This article presents secondary analyses from a randomized controlled trial, originally designed to determine the effects of a 6-month RT in combination with CR on body composition, body fat distribution, and the metabolic profile in a large cohort of overweight and obese menopausal women (14). The present study population consisted of 109 non-diabetic overweight and obese menopausal women aged between 46 and 70 years at baseline. We excluded subjects who did not complete the 6-month intervention. Consequently, data of 87 women were used for these secondary analyses.

Eligible participants met the following criteria: BMI between 27 and 40 kg/m2, no menstruation for 1 > year, having a follicle stimulating hormone level > 30 U/l, <2h per week of structured exercise, non-smoker, low to moderate alcohol consumers (≤ 2 drinks/day), and no use of hormone replacement therapy. All participants were apparently healthy and had no history or evidence on physical examination or laboratory testing of (i) cardiovascular disease, peripheral vascular disease, or stroke; (ii) diabetes (2h standard 75-g oral glucose tolerance test (OGTT)); (iii) severe hypertension (resting blood pressure >170/100mm Hg); (iv) orthopedic limitations; (v) body weight fluctuation >5 kg in the previous 6 months; (vi) uncontrolled thyroid or pituitary disease; and (vii) medication that could affect cardiovascular function or metabolism. The study was approved by the Université de Montréal ethics committee. After reading and signing the consent form, each participant was submitted to a series of tests.

Weight stabilization period

Before and after the 6-month weight loss protocol, subjects were submitted to a weight stabilization period (±2 kg of body weight) before testing. The goal of this approach was to stabilize the various metabolic variables of interest that could be altered by body weight fluctuations.

Caloric restriction intervention

Study participants entered a 6-month weight loss program aimed at reducing body weight by 10%. To determine the level of CR, 500 to 800 kcal were subtracted from baseline resting metabolic rate (determined by indirect calorimetry) multiplied by a physical activity factor of 1.4, corresponding to a sedentary state (15).

Macronutrient composition of the diets was standardized: 55%, 30% and 15% of energy intake from carbohydrates, total fat and proteins accordingly to the American Heart Association (16). Each participant met with the study dietitian to receive the diet prescription and recommendations. In addition, participants were invited to meet bi-monthly with the study dietitian for nutrition classes of 1-1.5 hours. All participants in the CR group were instructed not to change their usual daily physical activity habits during the weight loss protocol.

Exercise intervention

The 6-month RT program consisted of four progressive phases and was performed weekly on 3 nonconsecutive days under the supervision of an exercise physiologist, as previously described (14). The workload was adjusted by the exercise physiologist (when necessary) to maintain the intensity prescribed. Lower body and upper body strength was assessed using leg press and bench press weight training equipment from Atlantis Precision Series (Atlantis Inc., Laval, Que.).

Each training session included a warm-up of low intensity walking on a treadmill for 10 min. The RT program consisted of the following exercises: 1) leg press; 2) chest press; 3) lateral pull downs; 4) shoulder press; 6) arm curls; and 7) triceps extensions. These exercises provide a total body RT program for all of the major muscle groups of the body.  

Anthropometric and body composition measures

Body weight was measured to the nearest 0.1 kg on a calibrated balance (Balance Industrielle Montréal, Montréal, Québec, Canada) and participant’s height was obtained with a standard stadiometer (Perspective Enterprises, Portage, Michigan, USA). Waist circumference (WC) was measured using a measuring tape to the nearest 0.1 cm at the highest point of the iliac crest at minimal expiration. Total fat mass (FM), percentage of FM (%FM) and total lean body mass (LBM) were measured using dual energy X-ray absorptiometry (DXA) (General Electric Lunar Prodigy, Madison, Wisconsin; software version 6.10.019), as previously described (17). During the procedure, participants were asked to wear only a standard hospital gown while in the supine position. Calibration was executed daily with a standard phantom. In our laboratory, the intra-class coefficient correlation for test–retest for FM and LBM was 0.99 (n = 18).

A CT scanner (GE LightSpeed 16, General Electric Medical Systems, Milwaukee, WI) was used to measure the VF and the abdominal subcutaneous fat (AScF) area. Participants were examined in the supine position with both arms stretched above their head. The position of the scan was established at the L4-L5 vertebral disc using a scout image of the body (17). We quantified VF by delineating the intra-abdominal cavity at the internal most aspect of the abdominal and oblique muscle walls surrounding the cavity and the posterior aspect of the vertebral body. The AScF area was quantified by highlighting fat located between the skin and the external most aspect of the abdominal muscle wall. Deep AScF (DAScF) and superficial ScF (SAScF) areas were measured by delineating the subcutaneous fascia within the AScF and by computing areas of the layers of fat on each side of the fascia. The cross-sectional areas of fat were highlighted and computed using an attenuation range of -190 to -30 Hounsfield Units (HU).

Muscle attenuation (MA) was calculated by delineating the regions of interest and then computing the surface areas using attenuation range of -190 to -30 HU for fat, and 0 to 100 HU for skeletal muscle. In our laboratory, test-retest measures of the different body fat distribution indices on 10 CT scans yielded a mean absolute difference of + 1%.

Characterization of subjects

Participants were first randomly assigned to one of the two groups [CR (n= 52) or CR+RT (n= 35)]. For the present secondary analyses, participants were characterized as DYN or NDYN.  Since a correction for anthropometric variability has been recommended to define dynapenia (5, 18), we computed a muscular relative strength index with the ratio of strength (lower body strength + upper body strength) on BMI (19, 20). We included both measures of lower and upper extremity muscle strength since previous studies suggested that the rate of age-associated decline in muscle strength is quite different in these two anatomic regions (21).  Women in the lowest tertile of muscular relative strength index were considered DYN, while those in the second and third tertiles were considered as NDYN. In our sample, the cutoff point was 4.86 kg/BMI. Four groups of subjects were then created [group 1: CR/DYN (n= 13); group 2: CR/NDYN (n= 48); group 3: CR + RT/DYN (n= 18); group 4: CR + RT/NDYN (n= 30)].  

Fasting blood samples

Venous blood samples were collected to measure fasting total chol, HDL-chol, LDL-chol, triglycerides (TG), glucose and insulin levels after a 12-h overnight fast. Plasma was analyzed on the day of collection. Analyses were done on the COBAS INTEGRA 400 (Roche Diagnostic, Montreal, Canada) analyzer for total cholesterol, HDL-chol, triglycerides and glucose. Total chol, HDL-chol and TG levels were used in the Friedewald formula (22) to calculate LDL-chol concentrations. Insulin levels were determined by automated radioimmunoassay (Linco Research Inc. (St-Charles, MO, USA). Serum high-sensitivity CRP (hs-CRP) concentrations were assessed by immunonephelometry on IMMAGE analyzer (Beckman Coulter, Villepinte, France).

Glucose disposal

The test began at 07h30 after a 12-h overnight fast, as previously described by DeFronzo et al. (23). An antecubital vein was cannulated for the infusion of 20 % dextrose and insulin (Actrapid®, Novo-Nordisk, Toronto, Canada). The other arm was cannulated for sampling of blood. Plasma glucose was measured every 10 min with a glucose analyzer (Beckman Instruments, Fullerton, CA) and maintained at fasting level with a variable infusion rate of 20 % dextrose. Insulin infusion was initiated at the rate of 75 mU/m2/min for 180 min. Glucose disposal was calculated as the mean rate of glucose infusion measured during the last 30 min of the clamp (steady state).

Resting blood pressure 

Sitting blood pressure was measured in the left arm after participants rested quietly for 10 min using a Dinamap automatic machine (Welch Allyn, San Diego, CA, USA). An appropriate cuff size was selected for each subject based on arm circumference. Procedure was carefully standardized (24). 

Statistical analyses

Data in tables are presented as means ± standard deviation (SD). Univariate Analyses of Variance (ANOVA) were performed to compare means for each variable of interest at baseline and after the intervention. Repeated ANOVA analyses were performed to quantify the effect of treatment. Then, the Games-Howell test was used for posteriori group comparisons when a main model effect was noted. P-value of ≤0.05 was considered statistically significant. Statistical analyses were performed using the SPSS Statistical Package (version 15.0, SPSS, Chicago, Il, USA).

Results

Anthropometric measures and body composition 

No differences were observed at baseline among groups for anthropometric and body composition variables, with the exception of muscle attenuation (P= 0.03) (Table 1). Body weight, BMI, WC, FM, FMI, LBM, LBMI, AScF and VF significantly and similarly decreased in the four groups after the intervention (all P≤ 0.05).

Table 1 Groups’ comparisons for body composition and body fat distribution

Values are means ± standard deviation (SD); Δ = delta; BMI= body mass index; LBM= lean body mass; LBMI= LBM index, FM= fat mass; FMI= FM index; CT= computed tomography; AScF= abdominal subcutaneous fat; VF= visceral fat; MA= muscle attenuation; *= Do not include bone mass; NS= non-significant; Dynapenic ≤ 4.86 kg/BMI; Non-Dynapenic > 4.86 kg/BMI.

Metabolic profile 

No differences were observed at baseline among groups for the metabolic profile. TG, TG/HDL-chol ratio, fasting insulin, glucose disposal, relative glucose disposal and diastolic blood pressure significantly decreased in the four groups after the intervention (all P≤ 0.05); with no difference among groups. No improvement was observed in any groups for hs-CRP, IL-6, total cholesterol, HDL-chol and LDL-chol, Chol/HDL ratio, fasting glucose and systolic blood pressure after the interventions.

Table 2 Groups’ comparisons for metabolic profile

Values are means ± standard deviation (SD); Δ = delta; HR= heart rate; IL-6= interleukin-6; Chol= cholesterol; HDL= high-density lipoprotein; LDL= low-density lipoprotein; NS=non-significant; Dynapenic ≤ 4.86 kg/BMI; Non-Dynapenic > 4.86 kg/BMI.

Muscle strength 

By design, strength variables were significantly different between DYN and NDYN groups at baseline (all P≤ 0.001); with significantly higher values in NDYN groups (Table 3). All measures of strength were significantly improved in RT groups (DYN and NDYN subjects) and the CR-DYN group after the intervention (all P≤ 0.001); with greater improvements in the CR+RT/NDYN group compared to the others (all P≤ 0.001). Moreover, a significant decrease for all the measures of strength was observed in the CR/NDYN group compared to the CR+RT/NDYN group following the intervention.

Table 3 Groups’ comparisons for measures of strength

Values are means ± standard deviation (SD); Δ = delta; a = significantly different from Diet/Dynapenic; b = significantly different from Diet/Non-Dynapenic; c = significantly different from Diet + Resistance training/Dynapenic; d = significantly different from Diet + Resistance training/Non-Dynapenic; Dynapenic ≤ 4.86 kg/BMI; Non-Dynapenic > 4.86 kg/BMI.

 

Discussion

The aim of this secondary analysis was to compare the effect of a 6-month lifestyle intervention on body composition, the metabolic profile, and strength variables between DYN and NDYN overweight and obese menopausal women. We hypothesized that interventions aimed to increase muscle strength and decrease obesity levels would have greater effects on the metabolic profile and muscle strength in DYN overweight and obese women. Results from the present study showed that both DYN and NDYN obese women improved similarly body composition and the metabolic profile following CR alone or in combination with RT. However, the addition of RT to CR has superior beneficial effect on muscle strength.

As previously mentioned, there is only one study that directly compared the effect of CR and RT on the combined condition of obesity and dynapenia on body composition, metabolic profile and strength in older women (13). Their results showed that both CR and CR+RT groups improved several variables of the metabolic profile to the same extent (total chol, TG and systolic blood pressure) after the intervention. They showed that a moderate weight loss (≈5 kg) was associated with significant improvements in the metabolic profile. Our results support their findings. Of all metabolic components measured in our study, we observed similar improvements for TG, TG/HDL ratio, glucose homeostasis (fasting insulin, glucose disposal (mg/min/kg) and relative glucose disposal) and diastolic blood pressure to the same extent in DYN and NDYN women following both interventions. Moreover, the addition of RT to the diet had no supplementary value on the metabolic profile in the present study. Overall, our results are in line with previous studies in overweight menopausal women (25) and DYN obese older women (13).

Although weight-loss therapy is recommended to improve obesity-related metabolic complications, a prevailing concern in the clinical community is that the use of CR alone could have negative effects on LBM (26). In fact, it is recognized that CR induced weight loss results in a decreased LBM, which correspond in general to approximately 25% of total body weight loss (27). Furthermore, it has been reported that the addition of RT can attenuate this loss by half (28). RT has also been proposed to be an interesting approach to counteract the decrease in LBM observed in older adults, and particularly during caloric restriction-induced weight loss (29). Our data showed however that CR was associated with a reduced LBM to a similar extent to CR+RT in our DYN and NDYN obese women. This result is in disagreement with those of Frimel et al. (30), which is the only other study comparing CR to CR+RT in older (70 ± 5 yr) obese (BMI 37 ± 5 kg/m2) adults. They showed significantly greater decreases in LBM in the CR only group compare to the CR+RT (3.5 ± 2.1 vs. 1.8 ± 1.5 kg; P= 0.02). Regarding the absence of difference in LBM loss between the CR vs. CR+RT in our study, it is important to note that even though RT is known to be a potent stimulus for acute increases in circulating anabolic hormones such as testosterone, growth hormone and insulin-like growth factor-1 in men (31), the increase in anabolic hormones is minor or absent in older women following 6-month RT (32). A low level of testosterone in older women may be a limiting factor for muscle hypertrophy in response to RT (32), and hence could partly explain why we did not observe an increase or a lower reduction in LBM following RT. Furthermore, our results may also suggest an age-related resistance to alterations in metabolic function in response to RT. This assumption is supported by Dionne et al. and Hakkinen et al. (33, 34) who previously observed that older women experience significantly lower increases in LBM compared to younger women following a 6-month RT program.

Significant changes were also observed in our study for body weight, BMI, WC, FM, VF and AScF; which significantly and similarly decreased in DYN and NDYN obese women after both interventions. These results are in agreement with those of Senechal et al. (13) who showed similar decreased in body weight and trunk FM between CR or CR+RT in DYN obese women. Finally, Frimel et al. (30) also observed similar losses in body weight and FM following CR and CR+RT in frail obese older adults.

The progressive decline in muscle strength is perhaps the most ineluctable anatomical change occurring with aging. While muscle strength and muscle mass are related, it has previously been suggested that muscle quality (e.g., strength) is more important than muscle quantity (e.g., mass) in aging humans (35) as a determinant of functional limitation and poor health in older age (5, 21). Although the loss of LBM was not prevented with RT in our study, RT was still associated with increases in muscle strength in DYN women. These findings demonstrate that despite a decrease in LBM induced by CR, it did not translate into a decrease in muscle strength in DYN women. Very few studies have reported the effects of weight-loss intervention on muscle strength or muscle quality in obese women (36). Our results are in line with those of Wang et al. (36) showing that CR induced weight loss combined with moderate strength training maintained absolute knee extensor muscle strength in older persons with osteoarthritis. Like our results, these effects occurred despite a significant loss of LBM during the intervention. Taken together, our findings suggest that other factors than muscle mass contribute to gains in muscle strength in older obese women following a RT program. Finally, muscular strength also appears to be an important protecting factor for cardiometabolic health (37). Actually, some cross sectional and prospective data have showed an inverse association between strength and cardiometabolic risk factors (7, 12). However, our data do not showed a superior beneficial effect of RT on the metabolic profile.

Our study presents limitations. First, generalization of our data applies only to non-diabetic, sedentary, overweight and obese menopausal women. Second, the small number of participants in each group limits the power of the study. Third, comparisons with other studies are difficult because of the use of different cut off points for defining dynapenia (5). For example, the Foundation for National Institutes of Health Sarcopenia Project (FNIH) recommends the use of a single measure, grip strength, to characterize and individual’s overall strength status (38). However, it has been observed that the use of a single action (such as grip strength) may not always be a valid representative of and individual’s overall strength (39). Hence, the combination of upper and lower body strength might have superior potential value as an indicator of overall strength than handgrip strength alone (39). Fourth, the relatively normal metabolic profile at baseline in our subjects is likely to explain the absence of effect on total cholesterol, HDL-chol, LDL-chol, fasting glucose and resting systolic blood pressure observed. Five, measures of muscle fiber types and areas, capillaries, biochemical properties of skeletal muscle and hormonal profile would have been interesting. Finally, although another study from the MONET cohort examined the relationship between muscle strength and metabolic disturbances (insulin sensitivity) (40), its design was cross-sectional and participants were not categorized as DYN or NDYN. Hence, we believe our findings add to the body of literature regarding the effects of lifestyle intervention in DYN overweight and obese women.

Despite limitations, strengths of our findings include the use of a randomized design as well as the use of gold standard techniques available for the measurement of body composition, body fat distribution and cardiometabolic profile. We also used a 1-month weight stabilization period before testing to minimize the impact of body weight fluctuations on the metabolic profile. Finally, the use of the lowest tertile of strength is a relatively simple measure, which enhance the application in clinical practice (41). Overall, we consider that the methodology used strengthens the validity of our results.

In conclusion, results from the present study show that weight loss following CR and RT improves similarly the metabolic profile and body composition in DYN and NDYN overweight and obese menopausal women. The addition of RT had no additional effect on body composition and the metabolic profile, but was associated with improved strength in DYN and NDYN women despite losses of LBM. Further studies are needed to evaluate the effect of lifestyle interventions on the metabolic profile of individual with DYN phenotype.

Acknowledgements: RRL is a senior FRQS (Fonds de Recherches en Santé du Québec). MS is supported by the Manitoba Health Research Council, the Canadian Institute of Health Research (CIHR), and by the CIHR-Integrated and Mentored Pulmonary and Cardiovascular Training (CIHR-strategic Training Program). The Montreal Ottawa New Emerging Team in Obesity Group thanks Lyne Messier (study coordinator, Registered dietitian); Maxime St-Onge, Benoit Tousignant, and Philippe Carrier (training supervision); Isabelle Vignault and Jennifer Levasseur, R.N.; and the patients for their exceptional involvement in this study. This work was supported by grants from the Canadian Institute of Health Research (CIHR) New and Emerging Teams in Obesity (Université de Montréal and University of Ottawa; Montreal Ottawa New Emerging Team in Obesity project). OHN—63279 The MONET group thanks patients for their exceptional involvement in this study.

Conflict of Interest: The authors declared no conflict of interest.

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ASSOCIATION OF GRIP AND KNEE EXTENSION STRENGTH WITH WALKING SPEED OF OLDER WOMEN RECEIVING HOME-CARE PHYSICAL THERAPY

R.W. BOHANNON

Department of Physical Therapy, College of Pharmacy & Health Sciences, Campbell University, Buies Creek, North Carolina, USA.

Corresponding author: Department of Physical Therapy, College of Pharmacy & Health Sciences, Campbell University, 191 Main Street, Buies Creek, North Carolina 27506, USA. Phone: +1 (910) 814-4951; Fax: +1 (910) 814 4951; e-mail: bohannon@campbell.edu

J Frailty Aging 2015;4(4):181-183
Published online October 16, 2015, http://dx.doi.org/10.14283/jfa.2015.74


Abstract

Background: Decreased muscle strength and limited physical performance are key elements of frailty and sarcopenia. The relative value of grip and knee extension strength for explaining walking performance has not been clearly established. Objectives: Compare the ability of grip and knee extension strength to explain gait speed. Design: Retrospective use of cross-sectionally obtained data. Setting: Patients’ homes. Participants: Forty-four ambulatory women patients at least 65 years of age. Measurements: Grip and knee extension forces obtained bilaterally with dynamometers and comfortable gait speed. Results: Knee extension forces were, but grip strength forces were not, correlated significantly with gait speed. Knee extension forces were able, but grip strength forces were not able, to satisfactorily identify patients with gait speeds < .40 m/sec. Conclusions: For women receiving therapy in a home-care setting, physical performance as reflected by gait speed is better explained by knee extension strength than by grip strength.  

Key words: Muscle strength, gait, aging.


Introduction

Grip strength and gait speed are two easily measured physical performance variables used to identify older adults with frailty (1) or sarcopenia (2). Both performance-based measures have been proposed for use as vital signs for screening older adults (3, 4).  Several groups of investigators have recommended grip strength as a “predictor” of mobility limitations (eg, reduced gait speed) among older adults (5-7). This recommendation notwithstanding, grip strength is clearly not causally related to gait speed. Grip strength, on the other hand, is related to knee extension strength (8, 9), which is in turn a logical and proven explanator of gait speed (10, 11). Alley and associates have posited that grip strength and knee extension strength may explain “a similar amount of variance in walking speed (12).” Whether this is the case for older adults undergoing rehabilitation in various settings is not established. I, therefore, conducted this retrospective study to determine the relative value of various grip strength and knee extension strength measures for explaining gait speed in a sample of older women participating in physical therapy in a specific setting (homes).  My expectation was that knee extension strength would be more strongly related than grip strength to gait speed.  

Methods

This study involved use of a database of personal patients seen consecutively in a home-care setting by the author between 2001 and 2015. The study was limited to women patients at least 60 years of age who could follow multipart instructions. Patients were excluded if they had an acute problem (eg, recent fracture or joint replacement) that contraindicated or precluded the testing of knee extension strength or if they required more than contact guarding during walking. Retrospective use of the data without written consent was approved by the University of Connecticut Institutional Review Board (H10-316). 

Information regarding age, primary diagnosis, height and weight were obtained from the patients’ referral documents, self-report or actual measurement. Isometric strength measures were obtained bilaterally with calibrated dynamometers. Hand-grip strength was measured with a Jamar hand-grip dynamometer in the second handle position while patients were seated and their elbows were flexed 90 degrees in accordance with the recommendations of the American Society of Hand Therapists (13). Knee extension strength was measured with a MicroFET hand- held dynamometer using a make-test while patients were seated with their knees flexed 90 degrees (14). Comfortable gait speed was measured over the maximum linear distance available in each patient’s home setting (15). The actual timed distance ranged from 2 to 6 meters with at least .5 meters allowed for acceleration and deceleration.

All analysis was conducted using the Statistical Package for the Social Sciences (version 22.0) or MedCalc programs. Grip and knee extension strength data from each side were used, but the best of the 2 sides and the sum of the 2 sides were also used. Gait speed in centimeters/second was derived from timed distance measures. Gait speed was also dichotomized as less than versus greater than or equal to 40 centimeters/second (ie, the cut-point for household versus limited community ambulation) (16). Following the calculation of descriptive statistics, the relationships of specific grip strength and knee extension strength measures with gait speed were determined using Pearson correlations. The ability of grip and knee extension strength to identify gait speed differentiated household and community ambulators was examined using receiver operating characteristic curve (ROC) analysis.  As numerous hypotheses were tested a conservative significance level of p ≤0.01 was used.

Results

This study involved 44 women patients, a sample exceeding the 42 estimated to be necessary to achieve 80 percent power with p<0.01 for an effect size (correlation) of 0.50. The included patients could be classified as having had problems that were orthopedic (n=9), infectious (n=8), cardiovascular (n=6), fall-related (n=6), cancer (n=6), neurologic (n=3), pulmonary (n=2), or other (n=4). Descriptive statistics for sample demographics and performance variables are summarized in Table 1.  Table 2 presents correlations between strength measures and walking speed. The correlations between grip strength and walking speed ranged from 0.139 (left) to 0.295 (best). None was significant at p ≤0.01. For knee extension strength the correlations with walking speed ranged from 0.419 (right) to 0.463 (combined). All were significant at p ≤0.01. The ROC analysis showed that the area under the curve for grip strength measures ranged from 0.615 to 0.685. No grip strength measure differentiated significantly (p≤0.01) between patients with gait speeds above versus below .40 meters/second. The ROC analysis showed the area under the curve for knee extension strength measures ranged from 0.738 to 0.810. All knee extension strength measures differentiated significantly (p ≤0.01) between patients with gait speeds above versus below 0.40 meters/second.  

Table 1 Descriptive Statistics for Study Variables

Table 2 Pearson Correlations (95% Confidence Intervals) Between Strength Measures and Walking Speed

*p ≤0.01

Table 3 Area under the Receiver Operating Characteristic Curve Analyzing the Relative Value of Strength Measures for Differentiating Patients with Gait Speeds Below versus at or Above 0.40 Meters per Second

Discussion

Based on the correlational analysis of the present study, knee extension strength appears to be superior to grip strength as an explanator of gait speed. This finding is at odds with the statement by Alley et al that grip strength explains “a similar amount of variance in walking speed compared with knee extension strength (12)”. The findings are also contrary to those of Martien et al. who determined that knee extension strength was no better than grip strength for explaining the walking performance (6- minute walk distance) of older adults residing in nursing homes or the community (17) Interestingly, they did find knee extension strength to be superior to grip strength for explaining the walking distance of older adults residing in an assisted living setting. For individuals living in that setting, the variance in walking distance explained was 39% and 15% for knee extension strength and grip strength, respectively. 

The ROC analysis of the present study also supports knee extension strength as more accurate than grip strength for identifying patients walking at speed (≥0.4m/s) sufficient for at least limited community ambulation. The 0.4m/s criterion was deemed more appropriate than the 0.6 m/s (18), 0.8m/s (12), or 1.0m/s (19) criteria used or recommended by others as the patients were receiving care at home rather than outside the home in a community setting.

The findings of this study as well as the logical connection between knee extension strength and gait speed, notwithstanding, the use of grip strength as an explanatory of gait speed may be justified. Grip strength and knee extension strength tend to be related (8,9). Correlations between the variables (between r=0.441 and r=0.535) were all significant (p≤0.003) in the present study. Moreover, hand-grip strength is more easily measured than knee extension strength. The dynamometers used to measure knee extension strength are more expensive than those used to measure grip strength. The validity of knee extension strength measurements can be compromised if the dynamometer or tested individual are not adequately stabilized.

This study had several limitations. Though sufficiently powered to obtain significant results, the sample size was small compared to other studies (12, 17). The sample was also limited to women patients seen by a single therapist in one type of setting. Some aspects of testing could not be standardized across home settings. Specifically variable were patient seating during the testing of knee extension strength and the surface and distance traversed during the testing of gait speed. These inconsistencies, while real, did not preclude the finding of significant relationships between knee extension strength and gait speed.  

Funding: None

Conflict of interest: None

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