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D. Tavoian1, D.W. Russ1,2, T.D. Law1, J.E. Simon1,3, P.J. Chase3, E.H. Guseman4,5, B.C. Clark1,6,7


1. Ohio Musculoskeletal and Neurological Institute (OMNI), Ohio University, Athens, USA; 2. School of Physical Therapy and Rehabilitation Sciences, University of South Florida, Tampa, FL, USA; 3. School of Applied Health Sciences and Wellness, USA; 4. Diabetes Institute, USA; 5. Department of Primary Care, USA; 6. Department of Biomedical Sciences, USA; 7. Division of Geriatric Medicine at Ohio University, Athens, OH, USA

Corresponding Author: Dallin Tavoian, Ohio Musculoskeletal and Neurological Institute (OMNI), Ohio University, Athens, USA, dt114412@ohio.edu

J Frailty Aging 2021;in press
Published online May 14, 2021, http://dx.doi.org/10.14283/jfa.2021.21



This Brief Report describes a pilot study of the effect of 12 weeks of stationary bicycle high-intensity interval training, stationary bicycle moderate-intensity continuous training, and resistance training on cardiorespiratory, muscular, and physical function measures in insufficiently-active older adults (N=14; 66.4±3.9 years; 3 male, 11 female). After baseline testing, participants were randomly assigned to one of the exercise groups. High-intensity interval training and moderate-intensity continuous training had small-to-large effect sizes on cardiorespiratory/endurance and physical function measures, but very small effect sizes on muscular measures. Resistance training had small-to-large effect sizes on cardiorespiratory, muscular, and physical function measures. This pilot study should be interpreted cautiously, but findings suggest that resistance exercise may be the most effective of the three studied exercise strategies for older adults as it can induce beneficial adaptations across multiple domains. These effect sizes can be used to determine optimal sample sizes for future investigations.

Key words: High-intensity interval training, exercise, aging, physical function, muscle.

Abbreviations: 4SST: four-square step test; 6MW: six-minute walk; ES: effect size; HIIT: high-intensity interval training; KE: knee extensor; MICT: moderate-intensity continuous training; RT: resistance training; VO2max: maximal oxygen consumption.



Despite well-documented muscular and cardiorespiratory health benefits that accompany regular exercise participation, most older adults are not engaging in exercise with the volume and/or intensity sufficient for maintaining physical function (1, 2). In fact, fewer than 13% of older adults meet the aerobic (150 minutes moderate intensity/week; e.g., walking, stationary bicycling) and muscle strengthening (2 days/week; e.g., weight lifting) guidelines concurrently, while only 31% meet one of the two (3). A more pragmatic approach that emphasizes a single exercise strategy with the greatest effect on overall health may be a reasonable solution to optimize outcomes and improve adherence (4).
High-intensity interval training (HIIT) is an exercise strategy consisting of short periods (10 seconds to 4 minutes) of vigorous exercise interspersed with low-intensity rest periods. It can improve cardiorespiratory fitness and lower cardiovascular disease risk equal to, or greater than, traditional aerobic training (5), and has also been shown to improve muscle strength in young adults (6). However, the potential for HIIT to induce muscular benefits in older adults has not been adequately explored. The aim of this study was to examine whether stationary bicycle HIIT was a more efficient standalone exercise strategy to improve cardiovascular and lower extremity muscular function than established muscle strengthening (resistance training; RT) or aerobic (moderate-intensity continuous training; MICT) programs in older adults.



An in-depth protocol for this study has been published previously (7), and only essential information is provided in this section. It should be noted that a sample size of 24 (n=8/group) was initially planned for this pilot study. However, restrictions on human subjects research associated with the COVID-19 pandemic prevented attainment of the recruitment goal. Thus, we only present descriptive statistics and effect size estimates in this Brief Report.

Participant characteristics

Twenty-two generally healthy but insufficiently active (i.e., not meeting either aerobic or muscle strengthening guidelines (7)) participants aged 60-75 years were recruited, enrolled, and randomized, with 14 (66.4 ± 3.9 years; 3 male, 11 female) completing the study. One was removed for starting a new blood pressure medication while on the study protocol, and seven others were interrupted prior to completion due to the COVID-19 pandemic and unable to resume the study. Written informed consent was obtained from each participant in accordance with the Declaration of Helsinki. Ethical Approval for this study has been obtained from the Ohio University Institutional Review Board. Baseline characteristics are shown in Table 1.

Table 1. Baseline and post-intervention characteristics

Data are means ± SD. 4SST, four-square step test; 6MW, six-minute walk; BMI, body mass index; ES, effect size; HIIT, high-intensity interval training; MICT, moderate-intensity continuous training; RT, resistance training; VO2max, maximal oxygen consumption. Effect sizes are classified as very small (0.01-0.19), small (0.20-0.49), moderate (0.5-0.79), large (0.8-1.19), and very large (>1.20)

Study Design

This study had a screening/baseline assessment period of three sessions, randomization into one of the three exercise groups, a 12-week exercise training period, and a post-intervention assessment period of two sessions (7). All exercises were performed on site three days per week and supervised by an exercise professional. Below we provide a brief description of the experimental procedures and training programs. We refer the reader to the Supplement as well as our previously published detailed protocol (7) for additional information.


Primary Outcomes

• Isokinetic Strength: Obtained at 60°/second from the non-dominant knee extensors.
• Maximal oxygen consumption (VO2max): Obtained during a graded cycle ergometry exercise test.
• Quadriceps muscle volume: Assessed from magnetic resonance imaging scans of the non-dominant leg.

Secondary Outcomes

• Isometric Strength: Obtained from the non-dominant knee extensors at 90° of knee flexion.
• Fatigue Resistance: Assessed through a series of 120 isokinetic leg extensions at 120°/second.
• Total Body Fat Mass: Obtained via whole-body dual-energy X-ray absorptiometry scans.

Physical Function Outcomes

• Six-Minute Walk (6MW): Completed on a 30-meter course.
• Four-Square Step Test (4SST): Performed in a four-foot by four-foot square split into quadrants.
• Grip Strength: Obtained with a Jamar hydraulic grip strength dynamometer at position II.
• Five-Time Chair Rise: Performed on a chair with the seat 18 inches from the ground.

Exercise Intervention

Each participant performed their prescribed exercise 3x/week for 12 weeks. Adherence was defined as an attendance rate ≥80% (i.e., attended 29 of 36 exercise sessions), which all participants achieved. Participants in the HIIT group performed all exercises on a stationary bicycle (Peloton Interactive, Inc. New York City, NY, USA). The duration of the HIIT sessions were half the duration of the MICT sessions. Participants in the MICT group used the same stationary bicycle setup as in the HIIT group. Participants in the RT group performed all exercises using free weights, machines, or body weight.

Statistical analysis

The planned analysis for this study was a one-way ANOVA to compare group means. However, because we could not complete the study due to COVID-19 our sample size is not adequately powered for this type of analysis. Therefore, descriptive statistics, percent change from baseline (primary and secondary outcomes), absolute change from baseline (physical function outcomes), and corrected Hedge’s g effect sizes for small samples are reported. Effect sizes were classified as very small (0.01-0.19), small (0.20-0.49), moderate (0.5-0.79), large (0.8-1.19), and very large (>1.20) (8). 95% confidence intervals for descriptive statistics can be found in the Supplemental Table S1.



High-intensity interval training had very small effects on muscular strength and mass (ES=-0.17 to 0.19), small-to-large effects on cardiorespiratory/endurance measures (ES=0.44 to 1.13), and moderate-to-large effects on most physical function measures (ES=0.50 to 1.08). MICT had very small-to-small effects on muscular strength and mass (ES=-0.04 to 0.21), very small-to-large effects on cardiorespiratory/endurance measures (ES=0.16 to 0.90), and very small-to-very large effects on physical function (ES=0.17 to 1.21). RT had small-to-large effects on muscular strength and mass (ES=0.28 to 0.99), small effects on cardiorespiratory/endurance measures (ES=0.39 to 0.41), and very small-to-large effects on physical function (ES=0.12 to 1.07). All results can be found in Table 1 and Figure 1. See Supplement for detailed adverse event and adherence outcomes.

Figure 1. Changes in primary (A-C), secondary (D-F) and physical function outcomes (G-I) after 12 weeks of HIIT, MICT, or RT

Open symbols are values for individual subjects and solid bars indicate group means. A) knee extensor isokinetic strength; B) absolute VO2max; C) muscle volume; D) knee extensor isometric strength; E) knee extensor fatigue resistance; F) total body fat mass; G) six-minute walk (6MW) distance; H) four-square step test (4SST) time; I) non-dominant hand grip strength; J) five-time chair rise time.



The purpose of this study was to compare the effect of stationary bicycle HIIT on cardiorespiratory/endurance and muscular strength and size measures, as well as physical function adaptations, to MICT or RT in generally healthy but insufficiently active older adults. Though terminated early due to COVID-19 restrictions, the diverse data that were collected allowed us to calculate effect sizes to power future investigations. First, HIIT had a greater effect on VO2max than MICT (ES=0.44 and 0.16, respectively), and a similar large effect on fatigue resistance (ES=1.13 and 0.90, respectively). MICT has long been promoted as an essential element in healthy aging (9), and it is becoming more and more clear that HIIT is also a safe aerobic exercise regimen that is highly effective at improving cardiac, respiratory, and metabolic function in an older adult population (10). A somewhat unexpected finding of this study, however, was the effect of RT on VO2max. The benefits of aerobic and resistance training have historically been considered independent of each other, and as such there has been relatively little attention given to the effects of RT on cardiorespiratory variables (4).
Stationary bicycling is an ideal form of aerobic exercise for older adults due to its effectiveness at inducing cardiorespiratory adaptations and the relative low risk of injury (11), and has also been shown to elicit strength improvements in older adults when used for MICT (12) or HIIT (13). We expected a similar response to our cycling protocols, however, our low-volume bicycle HIIT protocol had a very small effect on muscular strength and size at the group level. There was a diverse response to HIIT at the individual level– some participants showed substantial increases while others demonstrated substantial declines in muscle strength and size (Figure 1). It is unclear why our cycling protocols did not consistently result in improved strength, as has been reported previously (12, 13), although there are several methodological factors that may affect muscular adaptations (e.g., resistance, cadence).
Due to the relatively recent interest in HIIT for older adults there are few studies reporting effects on physical function measures, though those that do appear to indicate beneficial effects (13-15). This proof-of-concept pilot study demonstrates that HIIT had a large effect on 6MW distance and a moderate effect on grip strength and chair rise time, indicating that HIIT can improve physical functional capacity in older adults without overt physical function limitations. This may translate into substantial improvements in physical function capacity in mobility-limited older adults, and future work should investigate this possibility. In this study we chose a pragmatic approach wherein our participants followed national exercise guidelines; however, we should note that nuanced differences in training paradigms (e.g., different intensities or controlling for total volume, duration, or caloric expenditure) could have yielded different results.



HIIT is a time-efficient exercise strategy that has the potential to produce both cardiorespiratory and muscular improvements, but few groups have investigated this potential. Our low-volume HIIT protocol did not consistently induce muscular adaptations but did elicit effects on cardiorespiratory/endurance and physical function measures comparable to MICT with half of the time commitment. Additionally, RT had small-to-moderate effects on cardiovascular/endurance measures along with the expected larger effects on strength. Future work should include strength and physical function measures to better characterize the adaptations to HIIT in order to determine if it is an effective and efficient exercise strategy for healthy and mobility-limited older adults.


Funding: This work was supported, in part, by a pre-doctoral fellowship grant to D Tavoian from the American Heart Association (19PRE34380496). 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 Rachel Clift, Lynn Petrik, Cammie Starner, Simon Moskowitz, Caleb Moore, Erica Baker, and Sam McGee for their assistance with data collection and exercise supervision. This study is registered with clinicaltrials.gov (NCT03978572).

Conflicts of Interest: In the past 5-years, BC has received research funding from NMD Pharma, Regeneron Pharmaceuticals, Astellas Pharma Global Development, Inc., and RTI Health Solutions for contracted studies that involved aging and muscle related research. In the past 5-years, BC has received consulting fees from Regeneron Pharmaceuticals, Zev Industries, and the Gerson Lehrman Group for consultation specific to age-related muscle weakness. BC is a co-founder with equity of OsteoDx Inc. The other authors declare there are no conflicts of interest.

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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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 2021;10(3)226-232
Published online December 7, 2020, http://dx.doi.org/10.14283/jfa.2020.63


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.



“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.



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.



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.



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).


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.


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.



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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E. Patrizio1, R. Calvani2, E. Marzetti2,3, M. Cesari4

1. Azienda di Servizi alla Persona Istituti Milanesi Martinitt e Stelline e Pio Albergo Trivulzio, Milan, Italy; 2. Fondazione Policlinico Universitario «Agostino Gemelli» IRCCS, Rome, Italy; 3. Università Cattolica del Sacro Cuore, Institute of Internal Medicine and Geriatrics, Rome, Italy; 4. Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy.
Corresponding author: Enrica Patrizio, Azienda di Servizi alla Persona Istituti Milanesi Martinitt e Stelline e Pio Albergo Trivulzio, Milan, Italy, Email: patrizio.enrica@gmail.com

J Frailty Aging 2020;in press
Published online November 24, 2020, http://dx.doi.org/10.14283/jfa.2020.61



The evaluation of the physical domain represents a critical part of the assessment of the older person, both in the clinical as well as the research setting. To measure physical function, clinicians and researchers have traditionally relied on instruments focusing on the capacity of the individual to accomplish specific functional tasks (e.g., the Activities of Daily Living [ADL] or the Instrumental ADL scales). However, a growing number of physical performance and muscle strength tests has been developed in parallel over the past three decades. These measures are specifically designed to: 1) provide objective results (not surprisingly, they are frequently timed tests) taken in standardized conditions, whereas the traditional physical function scales are generally self- or proxy-reported measures; 2) be more sensitive to changes; 3) capture the real biology of the function through the assessment of standardized tasks mirroring specific functional subdomains; and 4) mirror the quality of specific mechanisms underlying more complex and multidomain functions. Among the most commonly used instruments, the usual gait speed test, the Short Physical Performance Battery, the handgrip strength, the Timed Up-and-Go test, the 6-minute walk test, and the 400-meter walk test are widely adopted by clinicians and researchers. The clinical and research importance of all these instruments has been demonstrated by their predictive capacity for negative health-related outcomes (i.e., hospitalization, falls, institutionalization, disability, mortality). Moreover, they have shown to be associated with subclinical and clinical conditions that are also not directly related to the physical domain (e.g., inflammation, oxidative stress, overall mortality). For this reason, they have been repeatedly indicated as markers of wellbeing linked to the burden of multiple chronic conditions rather than mere parameters of mobility or strength. In this work protocols of the main tests for the objective assessment of physical function in older adults are presented.

Key words: Physical function, physical performance, gait speed, muscular strength, comprehensive geriatric assessment, older adults.



The aging of the global population is accompanied by an epidemiological transition from infectious and communicable diseases to a growing burden of chronic diseases. Health status in older persons is determined by the complex interaction of multiple factors (multiple chronic diseases, psychological, social, and environmental factors), that is not captured by traditional paradigms based on the concept of standalone diseases. The most common manifestation of poor health status in this population is represented by the loss of functioning, decrease in the autonomy of mobility and activities of daily living (ADLs), till the onset of disability and dependence (1, 2).
The Comprehensive Geriatric Assessment (CGA), evaluating not only the presence of diseases, but also the individual’s functions (intended both as physical and cognitive abilities), psychological factors, and social aspects, is a diagnostic and therapeutic process able to objectively define the health status of the frail older individual and support the design of tailored plans of intervention (3).
Loss of muscle strength and decline of physical performance are critical elements to consider in the detection of important age-related conditions. The definition of physical frailty usually includes measurements of handgrip strength and gait speed. Consistently, physical performance measures, as gait speed, Timed Up-and-Go (TUG) test, and the Short Physical Performance Battery (SPPB) are useful instruments for the screening of frailty in the general population (4). The European Working Group On Sarcopenia In Older People (EWGSOP2) recently published the updated diagnostic criteria for sarcopenia, that include poor muscle strength, and reduced physical performance to define the presence of sarcopenia and quantify its severity, respectively (5–7).
A recent position paper of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO) working group on frailty and sarcopenia proposed a standardization of the clinical assessment of muscle function and physical performance in order to promote the diagnosis of these conditions and facilitate the design of care programs (8). Muscle strength was defined as “the amount of force a muscle can produce with a single maximal effort”. Physical performance, on the other side, is considered a rather multidimensional concept, a function of the whole body, resulting from the functioning of multiple organs and systems (e.g., musculoskeletal, cardiovascular, respiratory, central and peripheral nervous systems). Hence, poor physical performance can be considered an early marker of frailty and subclinical diseases. Muscular strength and physical performance measures are related to pathophysiological conditions (i.e., atherosclerosis, inflammation, reduction of aerobic capacities), and are proved to predict the risk of healthcare use (i.e., hospitalizations, institutionalization) and adverse events (i.e., falls, cognitive decline, disability, death) (9–12). At the same time, these measures may represent a target and marker of efficacy for preventive interventions, such as rehabilitative and physical activity programs, being sensitive to changes of the health status. Such predictive capacity is confirmed across large and different populations. Furthermore, being these tests very clinical-friendly, they have been gradually embraced in the daily routine by different disciplines and settings, from the primary care to oncology, from cardiology to surgery, in order to support the diagnostic and therapeutic process (13–16).
In the last years, a number of measures and tools have been developed for the assessment of physical function. The aim of this paper is to describe standard procedures guiding the administration of the most important measures of strength and physical performance. In particular, we here present how to administer the handgrip strength test, the gait speed test, and the 400-meters walking test (17–19). Other important and well-established instruments, as the SPPB and the TUG test are not object of the present work as detailed instructions and video tutorials are already available (https://sppbguide.com/, and https://youtu.be/BA7Y_oLElGY respectively) (20, 21).



The protocols here presented are routinely part of a standard geriatric evaluation and do not require any authorization by institutional human research ethics committees. All patients can undergo the following tests. Exclusion criteria are specified within each protocol.

Handgrip strength test

To perform the test, a regularly calibrated, handheld hydraulic dynamometer is recommended (the JAMAR dynamometer is considered the gold standard). Use the same chair for every measurement. Subjects reporting current flare-up of pain in the wrist or hand or has recently undergone to surgery of the hand or wrist should not be tested on the affected side.

1 Seat the participant in a standard chair. Instruct to place forearms resting on the arms of the chair, with wrist just above the end of the arm of the chair. Tell to keep the hand in a neutral position, with the thumb pointing upwards.
2 Show the subject how to use the dynamometer. Place your hand around the handle, putting the base with the thumb on one side, and the other four fingers on the other. Tell the participant that he/she will not feel the grips moving when squeezing but the device is working and measuring his/her strength. Demonstrate the subject that the tighter the grip, the better score is registered by the instrument. Caution the participant that the dynamometer is quite heavy.
3 Place the adjustable handle of the dynamometer in the second position from the inside, unlocking the clip located on the lower post and fitting the adjustable handle on the second space between the teeth of the post.
4 Give the dynamometer to the participant and make sure that the grip bars are at the correct distance (with the fixed handle resting in the middle of the palm and the movable part in the center of the four fingers). If the handle seems to be too large or narrow to allow the patient to squeeze comfortably, remove the dynamometer and adjust, widening or tightening the handle.
5 Support the base with the palm of the hand while the subject holds the dynamometer, being careful not to limit its movement. Allow the participant to try to squeeze to familiarize with the instrument.
6 Check that the peak needle is set to zero. If it is not, rotate counter-clockwise the small caster in the middle of the gauge to move it to zero.
7 Start the test with the right hand. Invite the participant to squeeze the handle as strongly as possible. Use standard encouragement to highly motivate the participant during the test (e.g. «Squeeze, squeeze, harder!»). Ensure the participant maintains the maximum isometric effort for at least 3-5 seconds. When the needle stops rising, invite the participant to stop squeezing.
8 Read grip strength in kilograms from the outside dial and record the result to the nearest 1 kg. After each reading, reset the peak needle to zero. Repeat the measurement at the left hand. Obtain three readings in total for each hand, alternating the sides. Allow 10 seconds rest between each measurement.
Note: the peak-hold needle automatically records the maximum result. The gauge presents two dials, the inner one registers the value in lb, the outside in kg.
9 The highest reading of the 6 measurements is reported as the final result. Ask for and report about the hand dominance (i.e. right, left or ambidextrous).
10 If the participant complains about pain, discontinue the test and repeat the assessment only on the other side. If pain appears at both hands, stop the test.

Gait speed

To perform the test, the subject should wear comfortable clothes and shoes (with low heels for women). Only a single straight cane may be used during the walk. If the person can walk a short distance without it, should be encouraged to do so. If a person is unable or uses a walker, he/she should be considered as presenting mobility disability. As such, although the test can still be conducted with the use of the device, the meaning of the results for this specific geriatric outcome might be of limited value.
1 To perform the test, get a stopwatch and mark a 4-meter track along a flat floor. Ensure that the walking course is devoid of obstacles and include at least an extra meter at each end (Figure 1).
2 Encourage the person to walk without using any assisting devices. During the test watch particularly closely participants who normally use them, to prevent falls.
3 Instruct the participant to stand with both feet touching the starting line, and to start walking at usual pace over the 4-meter course, after a verbal command (“Go”). The assessor will then show how to perform the test to the participant, again stressing the request of walking at usual pace without running.
Note: The individual should not be aware where the goal line is placed in order to avoid a possible reduction of the pace when approaching to it. However, the tape on the floor might provide an implicit goal to the participant. For this reason, the participant might be instructed at walking well past the line on the floor.
4 During the walk stay to the side and slightly behind the subject, outside of the participant’s visual field, in order not to set the pace, but remaining in a good position for the safety of the person.
5 Begin timing when the first foot starts to move across the starting line, and stop when the first foot crosses the 4-meter mark. Do not start the watch when saying the verbal command, but when the participant actually begins to move. Do not stop timing if the foot lands on the line but does not completely cross it.
6 Report the time of execution of the test and calculate the gait speed. Repeat the test a second time and use the fastest time as result.
Note: If there is a problem with the stopwatch or the examiner is not sure of the timing, the test should be repeated.

Figure 1
4-meter walking test. The walking course should be unobstructed. Timing begins when the first foot starts to move across the starting line, and should be stopped when the first foot crosses the 4-meter mark


400-meter walking test

To perform the test, the subject should wear comfortable clothes and shoes (with low heels for women). During testing, the use of walk assistive devices, other than a single straight cane, is not allowed. If the subject does not feel safe attempting the walking course without aids (i.e. walker, quad cane, crutch), do not administer the test.
The assessor must be completely familiar with the test procedures and practice before attempting to administer the test to a participant. Procedures should be clearly demonstrated to the participants before performing the test and they should be queried to ensure that they understand the instructions. To ensure reproducibility, it is imperative that all participants are given the same instructions and that quantitative measurements associated with the tests are made in a uniform manner.
1 Identify a 20-meter long track by marking it with small traffic cones. Make sure that the walking path is not obstructed and include at least an extra meter at each end. Get a stopwatch and position two standard chairs along the walking course in order to allow the subject to rest during the test, if necessary (Figure 2).
2 Conduct the subject to the starting line and instruct to stand in a still position behind the line. It is important to clarify the goal of the test to the participant, i.e. to complete the 400-meter course.
3 Before starting the test measure the radial pulse for 30 seconds and blood pressure.
4 Instruct the subject to walk at usual pace, without overexerting, back-and-forth the 20-meter track for ten times, in order to allow the participant to plan the activity and consequently organize the walking pace according to his/her own reserves.
5 When participant indicates to feel ready to begin, proceed with the test. Instruct the individual to start to walk down the corridor at the command “Go”, and turn around the traffic cones, generating a continuous loop. Start timing when the participant takes the first step.
6 Stay by the side and just behind the participant, outside the subject’s visual field, during the walk. Be close enough to be able to support the participant if manifests difficulty or risks to fall, but not so close to dictate the pace.
7 When the 4rth lap is completed, ask the participant to report the perceived exert, and record the corresponding score of the Borg index for dyspnea.
Note: The test should be conducted at usual pace and the final goal is to complete the 400-meter course and not to reach the maximal effort. The participant should not overexert, therefore, if the participant reports “hard” or “very hard” should be invited to reduce the effort. The measurement of vital signs (radial pulse and blood pressure) before starting and at the end of the test, as well as the administration of the Borg scale after 4 laps and at the end of the test provide additional information useful to guarantee the participant’s safety and provide insights about the undergoing aerobic stress.
8 At the end of each lap (20-meter back and forth), encourage the subject with standardized phrases and count the number of completed and remaining laps.
9 Provide the participant the cane if he/she asks for it during the test, or has the evident necessity to use it to complete the walk.
10 Allow the participant to stop the walk to rest at any time, but not to lean against the wall, other surface (desk, counter, etc.), or sit. After 30 seconds, ask the participant if he/she can continue walking. If it is possible, continue the test, otherwise another 30 seconds of rest, in standing position, are allowed. If the subject is unable to continue after a 60-second rest or needs to sit down, stop the test.
Note: There is no limit to the number of rest stops as long as they can complete the walk without sitting.
11 Stop the stop-watch when the participant completes 400 meters (10 laps, first foot touching the floor beyond the finish line) or after 15 minutes, even if the participant has not covered all the distance. Record the time or, in the second case, measure the accomplished distance.
12 Immediately stop the test if participant reports chest pain or tightness, dyspnea, feeling faint, dizzy, or lower limbs pain.
13 At the end of the test, record the Borg index score, the sitting radial pulse for 30 seconds and blood pressure. Record the number, timing, and reasons for the rest stops (fatigue, chest pain, feeling faint or dizzy, shortness of breath, or other).

Figure 2
400-meter walking test. A 20-meter long track should be identified by marking it with small traffic cones. The participant has to walk at usual pace back-and-forth the 20-meter track for ten times, turning around the traffic cones in a continuous loop. The two chairs should be positioned by the side of the walking course, in order to not obstruct the track, but close enough to be rapidly reached if the subject needs to rest and sit during the test


Importance and predictive value of the presented tests

Low grip strength was found to be associated with slow gait speed, incident dismobility, disability, functional dependence, cognitive impairment, depression, cardiovascular diseases, hospital admission, and mortality (all-cause mortality, cardiovascular and non-cardiovascular mortality), in both sexes and independently of age and comorbidities (22–25). This relationship is confirmed across different populations and times of follow-up. Rantanen and colleagues studied the relationship between the handgrip strength with incident mobility and functional limitations in a large population (8,006 men from the Honolulu Heart Program and the Honolulu Asia Aging Study) aged at baseline 45-68 years old, with a 25 years follow-up (26). They found a strong association between the muscle strength in midlife and the risk of becoming disabled over the long-term follow-up. The strongest participants (i.e., >42.0 kg) had a significantly better risk profile when compared with those with poorest results at the handgrip, even after adjustment for a number of confounding conditions (Table 1). These results may be explained by greater physiological reserves in these subjects. Dodds and colleagues recently pooled data of grip strength from 8 different studies conducted in Great Britain on the general population. A total of 49,964 persons were considered to produce life-course nomograms of handgrip strength. The generated curves described a three period-evolution, with an increase to peak in early adulthood (i.e., 51 kg between 29-39 years old for men, and 31 kg between 26-42 years old for women), broad maintenance through to midlife, and a declining phase at older age (27). Different cut points were identified in the literature for poor handgrip strength, ranging from 16 to 21 kg for women and 26 to 30 kg for men, defining the risk of adverse events. Values adjusted for BMI or height also exists (23). The EWGSOP proposed values for poor grip strength <27 kg for men and <16 kg for women (7). Data on sensitivity to change in grip strength are still limited and inconsistent, a change of 6 kg was proposed to be significant. Some studies considered also the effect size (difference between the mean/median values of grip strength at baseline and after an intervention, divided by the standard deviation/inter-quartile range of the baseline measurement), and a value of 0.2–0.5 has been considered as indicative of low responsiveness, 0.51–0.8 of moderate responsiveness, and >0.8 of high responsiveness (17).

Table 1
Relationship between the handgrip strength with incident mobility and functional limitations. Adapted from Rantanen
et al. JAMA 1999

Results from multiple logistic regressions testing the predictive capacity of midlife grip strength for functional limitation and disability at advanced age (n=3,218); highest tertile used as reference group. Adjusted for age, weight, height, education, occupation, smoking, physical activity, and chronic conditions (i.e., arthritis, chronic obstructive pulmonary disease, coronary heart disease, stroke, diabetes, and angina).


Gait speed is a strong predictor of negative health outcomes, independently of the presence of common medical conditions and disease risk factors. Many studies demonstrated a strong association with incident disability (intended both as loss of ADL independency and dismobility), cognitive decline and dementia, falls and related fractures, mortality, and healthcare utilization (e.g., hospitalization and institutionalization) (11, 18, 28). Although tested in very different populations (e.g., inpatients and outpatients, independent, frail, and disabled subjects), different walking distances, and studied outcomes, the prognostic value is very consistent (Table 2). Studenski and colleagues studied the relationship between gait speed and mortality in a pooled population of 34,485 community-dwelling older people derived from 9 studies (Cardiovascular Health Study, Health, Established Populations for the Epidemiological Study of the Elderly, Aging and Body Composition study, Hispanic Established Populations for Epidemiological Study of the Elderly, InCHIANTI Study, Osteoporotic Fractures in Men, Third National Health and Nutrition Examination Survey, Predicting Elderly Performance, Study of Osteoporotic Fractures). The Authors found an overall HR for survival per each 0.1 m/s faster gait speed of 0.88 (95% CI, 0.87-0.90; P <0.001) confirmed after further adjustment for sex, BMI, smoking status, systolic blood pressure, diseases, prior hospitalization, and self-reported health (overall HR 0.90; 95% CI, 0.89-0.91; P <0.001). They also estimated the median life expectancy based on sex, age, and gait speed, providing a sort of nomograms (29). The value of 0.8 m/s for a 4-meter distance was found to identify frail patients with a high sensitivity (0.99), moderate specificity (0.64), and a high negative predictive value (0.99), and has been chosen by the EWGSOP2 as cut-off to diagnose severe sarcopenia (7, 30). At the same time, in their systematic review of the literature, Abellan van Kan and colleagues identified multiple cut-points of gait speed related to adverse outcomes, categorizing older people as slow (<0.6 m/s), intermediate (0.6-1.0 m/s), and fast (>1.0 m/s) walkers, demonstrating a continuum gradient of risk ranging from very fit to mobility impaired subjects (11). Furthermore, gait speed at usual pace in a 4-meter walk demonstrated also to be sensible to changes, with 0.05 m/s defining a minimally significant change and 0.1 m/s indicating a substantial change, with a corresponding reduction of 17.7% in absolute risk of death when increases of this value (31).

Table 2
Gait speed and ADL or mobility disability. Adapted from G. Abellan Van Kan et al.
The Journal of Nutrition, Health & Aging, 2009

* These studies analyzed the risk of disability considering gait speed variation rather than a specific cutpoint, as mentioned in the last column of the table; Health ABC study: Health Aging and Body Composition study, CHS: Cardiovascular Health Study, WHAS-I: Women’s Health and Aging Study, Hispanic EPESE: Hispanic Established Population for the Epidemiological Study of the Elderly, RR: relative risk, HR: hazard ratio, OR: odds ratio, ADL: activity of daily living.


The ability to perform the 400-meter walking test in less than 15 minutes defines the presence of mobility disability. This distance, corresponding to the length of about two blocks in the United States, is considered the minimum walking distance needed to have an independent life. The limit of 15 minutes, corresponds to a gait speed of 0.4 m/s, proven to be incompatible with functional autonomy. This instrument has a strong predictive capacity for development of negative health events (disability, mortality). Although this test is mostly used as a dichotomous indicator (presence/absence of mobility disability), its predictive capacity has been established also in relation to some of the parameters characterizing specific aspects of the performance (e.g., mean gait speed, number of stops to rest). Vestergaard and colleagues studied the differences in mortality and functional impairment rates during a 3- and 6-year follow-up period in the InCHIANTI Study population, analyzing the walking time and the variability in lap time. They found these factors to be both a short- and long-term predictors of mortality, and rest stopping mostly a long-term predictor of mortality (Table 3) (32). In a second study, based on the LIFE-P study, they found that the risk of mobility disability at follow-up was higher in those taking longer to complete the baseline 400-MWT and among those who needed to rest during the test (risk adjusted for age, sex, and clinic site: OR 5.4; CI 2.7–10.9) (33).

Table 3
Risk of death according to 400-meter walk test characteristics. Adapted from Vestergaard et al. Rejuvenation research, 2009

The model is adjusted for age, sex, Mini Mental State Examination score, symptoms of depression, education, smoking, body mass index, being sedentary, number of comorbid conditions (max 10, hypertension, coronary heart disease, congestive heart failure, stroke, peripheral artery disease, diabetes, pulmonary disease, hip fracture, cancer, arthritis), and SPPB score; HR: Hazard Ratio, CI: Confidence interval



The protocols presented in this paper are an attempt to standardize the methods of administration of these measures, in order to provide comparable results. Although there is not a unique way to conduct the here described assessments, given the different clinical settings and research protocols in which they can be applied, some steps are recognized as critical and able to affect results.
The absolute values and precision of grip strength measurements can be influenced by aspects of the protocol, such as hand size and dominance, posture (of the whole body and position of joints of the upper limb), provided encouragement, and the use of the maximum or the mean grip strength values (17). The observance of definite instructions in these steps, as already highlighted in the review of Roberts and colleagues, is crucial to ensure homogeneous measures and the training of the examiner assume a special importance to guarantee the reliability of the test (17). Taken with a handheld hydraulic dynamometer, the handgrip strength test demonstrated to have a good test–retest reliability (Intraclass Correlation Coefficient, ICC ≥ 0.85) and an excellent inter-rater reliability (ICC 0.95–0.98) (8, 17). The use of a handheld hydraulic dynamometer (units in Kg) is, therefore, considered the gold standard, but, for patients with upper extremity impairment or musculoskeletal deformations or diseases (as rheumatoid arthritis, osteoarthritis, or carpal tunnel syndrome), may not guarantee an accurate measure of muscle strength and may lead to underestimations, because it can cause stress on weak joints. Other available instruments are pneumatic, which measure grip pressure, mechanical, and strain dynamometer. The dynamometer should be calibrated at least once per year.
Elements of variability in the execution of gait speed test are walk distances (4, 6, or 10 meters, 8 or 15 foots), a static or dynamic start for walking, the usual or maximal gait speed, and the use of walking aids. A distance of 4 meters has been demonstrated to be feasible in different clinical settings, with a better accuracy compared to shorter walks. Moreover, the same distance is one of the components of the SPPB, allowing to deduce comparable measures from the whole battery (11). However, the test is characterized by a ceiling effect in high functioning persons with a high baseline walking speed (8). For these reasons, longer versions of the gait speed test (e.g., using 6- or 10-meter tracks) have been developed and validated in the literature for allowing a better discrimination of results in very fit individuals. Given the growing use of photocell-based systems of measurement, the method here proposed give the chance to have comparable results. Timing can also be measured differently from how we presented in the protocol, as starting and stopping the watch when the foot lands beyond the starting and finish lines. Moreover, some studies report measures of gait speed in full movement, starting the time measurement after the first two meters of walking. However, including the phase of acceleration provides information regarding subject’s abilities of coordination and movement planning, that are influenced by conditions frequently affecting older persons (i.e. Parkinson disease and other movement disorders). In the systematic review of the literature conducted by Peels and colleagues, the use of a moving start showed no significant difference in gait speed compared to a static start. They also found in a single study that subjects using a walking aid (cane) have a slower gait speed compared to those without (34).
To ensure the reproducibility of the 400-meter walking test, the training of the examiner is critical, in order to provide the same instructions and encouragement to participants, and to avoid to affect the results of the test dictating the pace during the walk. To ensure the correct execution the assessment, is also important to respect the provided timing for the stop rest and for the whole test. Moreover, the possibility to use walking aids and to warm up can influence the performance. The 400-meter walking test also demonstrated a high test-retest reliability, but it is mostly applied in research setting, requiring a higher administration time and a bigger space to be performed. On the other hand, being a dichotomous measure able to identify mobility disability, it provides an important and easy-to-understand indication of fitness of the subject, useful to address treatments or other tailored interventions (35).
The hand-grip strength test has been found to correlate with strength of other muscle groups, thus a good indicator of overall strength. The sensitivity to changes of the gait speed, together with an excellent test-retest and inter-rater reliability (ICC, 0.96-0.98) make gait speed a good marker for efficacy of intervention programs and treatments. Test-retest reliability of gait speed has been confirmed across different populations, from healthy older adults, people with comorbidities, to patients affected by stroke, cardiovascular disease, COPD. Compared to other tests (SPPB, chair stand test), gait speed has a stronger or similar predictive capacity for adverse events (ADL and mobility disability, hospitalization, health decline). Composite measures, as the SPPB, may have a better prognostic value, especially for high performance subjects (10, 11). Moreover, a walking speed less than 0.5 m/s is highly predictive of inability to perform the 400-meter walking test. Being very easy to perform, even in restricted places, and with minimal risk, it may be used as an alternative indicator of mobility disability when the performance of the 400-meters walking test is not possible (35).
In conclusion, the strong predictive capacity for adverse outcomes of muscle strength and physical performance measures as well as the reliability and the high feasibility of these tools make them suitable for supporting clinical and research decisions. In particular, the assessment of these measures may support the development of person-tailored interventions aimed at preventing/managing age-related conditions, as frailty and sarcopenia. These measures can both identify subjects at risk (who may benefit from tailored interventions), especially in primary care, but also serve as markers for monitoring the efficacy of the decisions. The dissemination of their use in clinical and research setting with a standard procedure may permit an early application and monitoring of critical aspects of the wellbeing of older persons.


Funding: None.
Conflcit of interest: The authors have no conflicts of interest to disclose.



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L. Ma1,2,3, Z. Tang1,3, P. Chan1,3,4, J.D. Walston2,5


1. Department of Geriatrics, Beijing Geriatric Healthcare Center, Xuanwu Hospital, Capital Medical University, Beijing Institute of Geriatrics, Key Laboratory on Neurodegenerative Disease of Ministry of Education, Beijing 100053, China; 2. Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21224, USA; 3. National Clinical Research Center for Geriatric Disorders, Beijing 100053, China; 4. Department of Neurology and Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; 5. Older Americans Independence Center, Center on Aging and Health, Johns Hopkins University, Baltimore, Maryland 21205, USA.
Corresponding author: Dr. Jeremy D. Walston, Division of Geriatric Medicine and Gerontology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21224, USA. E-mail: jwalston@jhmi.edu; Dr. Zhe Tang, Beijing Geriatric Healthcare Center, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing 100053, China. Tel: 86-010-63162077. E-mail: tangzhe@sina.com.

J Frailty Aging 2019;8(1):33-38
Published online November 23, 2018, http://dx.doi.org/10.14283/jfa.2018.38



Background: Although frailty status greatly impacts health care in countries with rapidly aging populations, little is known about the frailty status in Chinese older adults. Objectives: Given the increased health care needs associated with frailty, we sought to develop an easily applied self-report screening tool based on four of the syndromic frailty components and sought to validate it in a population of older adults in China. Design: Prospective epidemiological cohort study. Setting: Community-dwelling residents living in Beijing, China. Participants: 1724 community-dwelling adults aged ≥60 years in 2004 with an 8-year follow up. Measurements: We developed a simple self-report frailty screening tool—the Frailty Screening Questionnaire (FSQ)—based on the modified Fried frailty components. The predictive ability for outcome was assessed by age and sex adjusted Cox proportional hazards model. Results: According to FSQ criteria, 7.1% of the participants were frail. Frailty was associated with poor physical function, fractures, falls, and mortality. Both frailty and pre-frailty were associated with a higher mortality rate: frailty—hazards ratio (HR), 3.94, 95% confidence interval (CI), 3.16–4.92, P<0.001; pre-frailty—HR, 1.89; 95% CI, 1.57–2.27, P <0.001; adjusted models for this variable did not affect the estimates of the association. Among the four frailty components, slowness was the strongest predictor of mortality. The combination of the four components provided the best risk prediction. Conclusions: FSQ is a self-report frailty measurement tool that can be rapidly performed to identify older adults with higher risk of adverse health outcomes.

Key words: Frailty, physical function, mortality.



One of the most commonly recognized risk states for adverse outcomes in older adults is frailty. Quality frailty measurement should be able to identify frailty and those frail older adults that might respond to treatment, predict adverse outcomes, and ideally be able to identify those with a common biological underpinning (1). Frailty is most often defined as a geriatric syndrome, resulting from a cumulative decrease in multiple physiological systems and consequent reduction in physical reserve and defense ability (2, 3). It is often accompanied by increased vulnerability to adverse outcomes including falls, disability, and mortality (2). The most common definition of frailty was proposed by Fried, who considered the clinical phenotype of frailty as a well-defined syndrome with biological underpinnings (3). The Fried frailty detection identifies frailty by evaluating symptoms and signs associated with biological aging, including shrinking, exhaustion, weakness, slowness, and low levels of activity (3). Other main frailty concepts are often measured by cumulative comorbidities or “deficits” (4). The deficit model assesses accumulated declines in multiple domains with regard to diseases, and physical, psychological, and social functions, and comprehensively captures comorbidity and disability.
Although the original Fried’s physical frailty phenotype scale remains the most validated and utilized method, self-report information on Fried components also showed good predictive ability (5, 6). Hence, a self-report frailty detection tool may provide an alternative method for rapidly screening large populations of frail adults. Although dozens of other measurement tools for frailty have been reported, frailty detection methods are recommended to be matched to a particular need or environment to be most effective (7).
When attempting to identify frailty detection methods applicable to Chinese older adults, it is evident that available screening tools present two major limitations. First, most are time-consuming and are difficult to apply in busy medical practices with large populations. Second, no tool to date has been developed specific for Chinese elders. Given the large number of older outpatients in Chinese health care settings, the use of a standardized subjective evaluation of frailty would likely be readily accepted and adopted by busy clinicians. To address the current lack of an easy-to-use, valid, reliable screening measure of physical frailty consistent with original conceptual and biological model, we developed and validated a simple frailty pre-screening tool for outpatient settings—the Phenotypic Frailty Screening Questionnaire (FSQ).




Data were from the Beijing Longitudinal Study of Aging, a longitudinal study funded by the United Nations Population Fund (UNPFA CPR/90/P23) in 1992 (8). A cross-sectional survey comprising 1865 adults aged ≥60 years was conducted based on sample data from the fourth census of Beijing in 2004. Well-established statistical sampling techniques, which included clustering, stratification, and random selection were applied. Details of the sampling scheme were described elsewhere (9, 10). 1724 participants completed the frailty assessment. Data were collected on the following aspects: socioeconomic and demographic characteristics, physical health (self-report history of chronic disease and clinical syndromes), physical function, life behavior and social function, neuropsychological health, and medical condition. The definitions of cognitive impairment and depression appear in our previous publication (11). The mortality data for all subjects were collected every year until the end of December 2012. Mortality ascertainment was 100% complete. Instances of death were confirmed by family members or neighborhood or village committees. This study was approved by the ethics review board of Xuanwu Hospital, Capital Medical University and all the participants provided informed consent.

FSQ assessment

The FSQ scale was developed to represent four of five components of the Fried criteria: slowness, weakness, inactivity, and exhaustion (Table S1). Slowness received a score of 1 if participants had difficulty walking 250 meters. Weakness received a score of 1 if participants had difficulty in lifting or carrying something weighing 5 kilograms. Exhaustion received a score of 1 for participants who responded yes to either “Everything I did was an effort” or “I could not get going” in the past week. Inactivity was measured by asking participants how many hours they had spent on weekly exercise; subjects who responded <3 hours/week scored 1 point. The FSQ total score is 0–4. A score of 0 was considered robust; 1–2 was considered pre-frail; and a score of ≥3 indicated frailty.

Physical function

We assessed physical function by means of the balance test, chair-stand test, activities of daily living (ADL), and instrumental activities of daily living (IADL) as well as in terms of fractures and falls.

Statistical methods

Statistical analyses were performed by SPSS 11.5 (SPSS, Inc., Chicago, IL, USA). Chi-square tests were conducted for discrete variables, and analysis of variance and Student t tests were used to compare means of the groups for continuous variables with Tukey post hoc tests. We evaluated survival using Kaplan-Meier curves stratified for different sex and age-groups. A Cox proportional hazards model was used to evaluate the effect of covariates (age, sex, and frailty) on mortality after testing for the proportionality assumption. We considered P <0.05 statistically significant.


Using the FSQ in the Beijing Longitudinal Study of Aging population, 194 participants were identified as frail and the prevalence was 11.3% (weighted, 7.1%). The prevalence of pre-frailty was 32.5% (weighted, 29.5%). Frailty was associated with female gender, rural residency, older age, and lower socioeconomic status. Higher prevalence of frailty was observed among participants who were not married, those with a history of heavy physical labor occupation, and those with poor health or life satisfaction (Table 1). For both men and women, the prevalence of frailty increased with age and was higher among rural residents (Table S2). Frailty was more common in subjects with chronic diseases (Table S3).

Table 1 Demographic characteristics of the frailty status defined by FSQ

Table 1
Demographic characteristics of the frailty status defined by FSQ



The prevalence of frailty components according to the FSQ included slowness, 15.3%; weakness, 19.0%; inactivity, 23.0%; and exhaustion, 21.9%. The prevalence of 0, one, two, three, and four components was 56.3%, 22.9%, 9.6%, 7.9%, and 3.4%, respectively. The prevalence of the four components was higher among women than among men (Table S4).
Compared with robust subjects, frail and pre-frail status was associated with poor balance and chair-stand performance, ADL dependency, IADL dependency, fracture and falls, even after adjustment for sex (but not fractures in male) (Table 2). Among both men and women, being frail or pre-frail was associated with 8-year mortality. The four components showed a higher mortality rate in the overall, female, and male samples (Table S5). Frailty and each of the four components were associated with mortality in every age-group (except inactivity in 60-69 years group and exhaustion in ≥ 80 years group) (Table S6).  Figures S1, S2 and S3 present Kaplan-Meier curves for the proportional survival of participants with different frail statuses in the different age- and sex groups. The unadjusted associations were significant for the predictive association of frailty and pre-frailty with mortality; after adjusting for age and sex, the 8-year mortality hazard ratio was 2.131–3.444 and 1.318–1.972, respectively, for frailty and pre-frailty. Each component could predict mortality—even after adjusting for age and sex. Slowness was the strongest predictor and exhaustion the weakest predictor. Combined, the four components offered best risk prediction for mortality than the single component (Table 3; Figure S4).

Table 2 Characteristics of physical functions in different sex according to the FSQ

Table 2
Characteristics of physical functions in different sex according to the FSQ

a: have a fracture in last two years. b: fall twice in the last year; Abbreviations: ADL, activities of daily living; IADL, instrumental activities of daily living.

Table 3 Predictive models of mortality at 8-year follow-up

Table 3
Predictive models of mortality at 8-year follow-up

Reference: Robust. Model 1: Unadjusted Cox proportional hazard analysis. Model 2: Adjusted Cox proportional hazard analysis. Adjusted for age and sex. Abbreviations: HR, hazard ratio; CI, confidence interval.



The FSQ is an easy to use self-report tool developed in a Chinese population. It was loosely derived from the phenotypic frailty detection method. This was developed in part because of the need for quick pre-screening tool for frailty in busy Chinese outpatient practices where up to 10 patients an hour may be seen. This study found the weighted prevalence of frailty based on the FSQ to be 7.1%. This is similar to the prevalence of frailty as measured using the Fried phenotype criteria in China (7.0%) (12). Most data on the prevalence of frailty in the Chinese population have been based on frailty index conceptual model. We previously reported the prevalence of frailty based on frailty index to be 8.8% in the China Comprehensive Geriatric Assessment Study and 9.1% in the Beijing Longitudinal Study of Aging II (13, 14). In this study, the prevalence of frailty based on the FSQ was found to be higher in women and increased with advancing age, consistence with previous studies (3, 13, 15–17). One meta-analysis confirmed the pattern of sex differences in frailty and mortality to be a “male-female health-survival paradox” (18).
We found that slowness was the highest predictor among the four components. This result constitutes a response to the question as to which component of the phenotype model is more informative with regard to frailty assessment. Another investigation found gait speed to be the best indicator of frailty and that the combination of gait speed and physical activity was the most informative among the Fried components (19). Several studies have determined gait speed to be the preeminent frailty screening tool (20–22). Gait speed is a simple, acceptable measurement that can be easily performed in a routine clinic. The present investigation provides evidence that among the four components, self-report slowness is also the most important indicator for mortality in older subjects.
We compared the new tool with other instruments reported in the literature in terms of the following five aspects: population; frailty components; ease of application; primary use; and validity (Table S7). Among the eleven self-report instruments in the comparison, the FSQ was one of only two tools which were based on physical frailty and showed validity in outcome prediction in a large population.
The present study’s strengths include the large sample and completeness of the long-term follow-up. The Beijing Longitudinal Study of Aging is based on a large population-based cohort using clustering, stratification, and random-selection sampling techniques; thus, it can be taken to be representative of older Chinese people (8). Moreover, in the 8-year follow-up, mortality ascertainment was 100% complete. The present study also addressed the question as to which component of the phenotype model was more important. As shown in Table S7, the FSQ is quick to use by non-specific staff, and it is available from routinely comprehensive geriatric assessment data. Last and the most important, this study shows that the FSQ is feasible for a Chinese population. To the best of our knowledge, the FSQ tool is the only assessment tool based on the frailty phenotype designed for screening frailty in a Chinese population.
Our study also has several limitations. One of the main limitations is the lack of objective measurements. Hence, we were unable to evaluate the five-item Fried Phenotype in comparative analyses. Future studies on validation of FSQ with measured Fried phenotype should be conducted. Second, we did not take into account potential changes in frailty status between visits. A scoring system is needed to capture the dynamic nature of frailty so that it can be used as an outcome and intervention measurement (23). Third, we demonstrated that the four self-report Fried frailty components do not play the same role in predicting mortality, and the total level of frailty is not equivalent to the sum of those components. Future studies should weigh those components, characterize the trajectories of frailty, and examine cross-cultural validation.



FSQ is a useful quick and feasible self-report frailty tool that has been demonstrated to predict mortality in Chinese old adults. To our knowledge, this study is the first to report the prevalence of frailty and long-term prognosis using a self-report version of the Fried phenotype in a large longitudinal Chinese population. The FSQ was gathered using information provide by participants; it is associated with physical function, chronic disease, fracture, falls, and mortality, and it shows a good agreement with prior studies in China using Fried phenotype. The results of this study may ease frailty screening in older Chinese population by offering a very simple way to identify frailty and related risk of mortality in older adults. This in turn may facilitate targeted comprehensive geriatric assessment for the frail subset of patients as has previously been recommended in the United Kingdom (24). In addition, it may facilitate the development of novel interventions to better manage frailty and slow  declines in health status.


Funding: This work was supported by United Nations Population Fund (CPR/90/P23) and Milstein Medical Asian American Partnership Foundation Project Award in Geriatrics.
Acknowledgement: We acknowledge all the people who participated in the cohort study.
Presented as poster in Society for Epidemiologic Research 51 Annual Meeting (SER2018), Baltimore, Maryland, USA, June 19-22, 2018.
Conflict of Interest: None.



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1. Division of General Internal Medicine and Clinical Innovation, New York University School of Medicine, New York, New York, USA; 2. Department of Population Health, New York University School of Medicine, New York, New York, USA; 3. Division of Geriatrics, New York University School of Medicine, New York, New York; 4. VA New York Harbor Healthcare System, USA; † Currently affiliated with Columbia University Medical Center, New York, New York, USA.
Corresponding author: Jeannette M. Beasley, PhD MPH RD, Assistant Professor, Division of General Internal Medicine and Clinical Innovation, NYU School of Medicine, 462 First Avenue, 6th Floor CD673, New York, NY 10016, T: 646-501-4681, jeannette.beasley@nyumc.org


J Frailty Aging 2018;7(3):182-186
Published online July 9, 2018, http://dx.doi.org/10.14283/jfa.2018.21



Background: Through diet and exercise interventions, community centers offer an opportunity to address health-related issues for some of the oldest, most vulnerable members of our society. Objectives: The purpose of this investigation is to draw upon nationwide data to better characterize the population served by the congregate meals program and to gather more detailed information on a local level to identify opportunities for service enhancement to improve the health and well-being of older adults. Design: We examined community center data from two sources: 2015 National Survey of Older Americans Act and surveys from two New York City community centers. To assess nationwide service delivery, we analyzed participant demographics, functional status defined by activities of daily living, and perceptions of services received. Measurements: Participants from the two New York City community centers completed a four-day food record.  Functional measures included the short physical performance battery, self-reported physical function, grip strength, and the Montreal Cognitive Assessment. Results: Nationwide (n=901), most participants rated the meal quality as good to excellent (91.7%), and would recommend the congregate meals program to a friend (96.0%). Local level data (n=22) were collected for an in-depth understanding of diet, physical activity patterns, body weight, and objective functional status measures. Diets of this small, local convenience sample were higher in fat, cholesterol, and sodium, and lower in calcium, magnesium, and fiber than recommended by current United States Dietary Guidelines.  Average time engaged in moderate physical activity was 254 minutes per week (SD=227), exceeding the recommended 150 minutes per week, but just 41% (n=9) and 50% (n=11) of participants engaged in strength or balance exercises, respectively. Conclusion: Research is warranted to test whether improvements in the nutritional quality of food served and access/supports for engaging in strength training within community centers could help older adults achieve diet and physical activity recommendations.

Key words: Aging, diet quality, cognitive function, physical function.




The number of Americans aged 65 years and older is projected to double from 49.1 million in 2016 to ~100 million by 2060 (1). The Older Americans Act (OAA) Title III, federal legislation first passed in 1965, established a grant system to fund programs such as congregate meals for adults aged 60 and over. Congregate meal services operate in all 50 states through over 5,000 providers. As part of the program, data are collected on demographics, functional status defined by activities of daily living (ADLs), and perceptions of services received. However, there are few data that address the efficacy of the program (2) or describe potential opportunities for enhancement of services. Prior local level studies have focused on factors associated with food insecurity (3, 4), dietary intake (5, 6), physical activity (7), and the built environment (8, 9). National studies have included commentaries on the perceived impact of the program (2, 10).
Community centers represent an opportunity to help older adults meet dietary recommendations and offer opportunities to engage in physical activity. The first large-scale diet and physical activity intervention trial among older adults recently demonstrated improved adherence to national dietary guidelines and delayed cognitive decline of a Finnish population (11). A multi-component intervention conducted in the United States testing a diet consistent with the US Dietary Guidelines, the Dietary Approaches to Stop Hypertension (DASH) diet, improved cognitive performance among adults (mean age 52, standard deviation 10 years) with prehypertension or stage-1 hypertension (12). The purpose of this investigation is to draw upon nationwide data to better characterize the population served by this program, and to gather more detailed information on a local level to identify opportunities for service enhancement to improve the health and well-being of older adults.



To obtain a nationally representative sample, we summarized the most recent data release (2015) of the National Survey of Older Americans Act, a telephone survey that has been conducted annually since 2005. The weighting scheme samples Department of Health and Human Services-funded Area Agencies on Aging. Within selected programs, a sample of clients for each service is surveyed. Services include the Home Delivered Meal Program, Homemaker Services, Transportation, Family Caregiver Support Program, Congregate Meals, and Case Management (13).
To obtain more detailed information on nutrition, physical activity, and functional status to inform intervention designs, we recruited a convenience sample of English-speaking adults over age 65 from two senior centers in New York City. We posted recruitment flyers in each senior center near the main dining areas with study details and contact information. Study staff provided additional announcements during lunchtime. At the first visit, participants were instructed to complete a four-day food record, including at least one weekend day. During the second visit, the food record was reviewed with a nutritionist and clarifications were noted on the form. We measured physical function via the validated RAND-36 (14) and objectively using the Short Physical Performance Battery, comprised of balance, gait, and lower extremity strength components (15). We measured grip strength using a Jamar hand-held dynamometer (Lafayette, IN) in the dominant arm for two trials. We measured cognitive performance using the Montreal Cognitive Assessment (MoCA)(16).
Food records were analyzed using Nutrition Data System for Research (NDSR 2016) (Nutrition Coordinating Center, University of Minnesota, MN)(17) Diet quality was assessed using a DASH score (18) comprised of nine components (total fat, saturated fat, protein, cholesterol, potassium, calcium, magnesium, sodium, and dietary fiber) that was adapted to accommodate the higher protein content of the OMNI-Heart protein-rich diet (25% of energy) to reflect the growing evidence suggesting protein needs are greater among older adults (19, 20). Descriptive statistics were used to characterize participant demographics (Table 1) and perceptions of services received (Table 2). Within the local sample, we further characterized diet (Table 3), and physical activity (Table 4),using mean and standard deviation for normally distributed nutrient density variables and median and inter-quartile range for physical activity variables as Shapiro Wilks results were p<0.05 . Data were analyzed using SAS (Version 9.4, SAS Institute, Cary, NC), and PROC SURVEYFREQ was used to account for the sampling design within the nationwide sample. The Institutional Review Board at New York University School of Medicine approved this study.



National (US) Data

Two-fifths of participants were between 65 and 74 years old (40.8% in US, Table 1). Approximately two-thirds were female and the sample was racially/ethnically diverse (Table 1). Less than one-fifth of the US sample completed college, and two-fifths of the US sample were married.

Table 1 Congregate Meals Participant Characteristics, National and Local Level

Table 1
Congregate Meals Participant Characteristics, National and Local Level

*Weighted to account for the sampling design within the nationwide sample


Over half (58.2%) reported no limitations in ADL’s (bathing, dressing, eating, transferring from bed to chair, or toileting) and just 16.2% reported 2 or more limitations. Participants rated the congregate meals program favorably. Most participants (91.7%) rated the overall quality of meals as good to excellent, and 96% would recommend the congregate meals program to a friend (Table 2). Almost three-quarters reported the meals improved their health (74.4%), four-fifths stated meals improved their diet (77.5%), and 81.5% stated meals helped them feel better.

Table 2 Participants’ Functional Status and Perceptions of the Nationwide Congregate Meals Program n=901

Table 2
Participants’ Functional Status and Perceptions of the Nationwide Congregate Meals Program n=901


Local New York City (NYC) Data

Less than one third of local NYC participants met any of the nutrient goals for the OMNI-Heart protein diet (Table 3). On average, saturated fat comprised 10% of energy compared to the recommended 6% of energy. Protein intake was 20.2% (SD=4.5%) of energy, which is lower than the 25% of energy target, and cholesterol intake was two times higher than the goal (145mg versus 71mg). Two-thirds (n=14) met the 2008 Physical Activity recommendation of engaging in 150 minutes per week of moderate physical activity (21). Less than half (n=9, 41%) engaged in strength exercises, and median frequency was less than the goal (0 versus 3 times per week, respectively)(22) (Table 4). Half (n=11, 50%) participated in activities that improve balance (e.g. yoga and tai chi) with an median frequency of one time per week, rather than the target of three times per week. Mean Body Mass Index (BMI) was 28.5 (SD=6.5), with over half categorized as overweight or obese (27.3% BMI 25-29.9 and 35.9% BMI 30+) (data not shown).

Table 3 Comparison of Diet Quality with OMNI-Heart Protein Diet (18, 31)

Table 3
Comparison of Diet Quality with OMNI-Heart Protein Diet (18, 31)


Table 4 Comparison of Physical Activity with Evidence-Based Intervention Goals (22, 32)

Table 4
Comparison of Physical Activity with Evidence-Based Intervention Goals (22, 32)



The congregate meals program is consistently popular among participants, with 92% rating the meals as good to excellent, serving a vulnerable population that is projected to double in size over the next 40 years. Despite the potential value of this program, less than a third of participants met any of the nutrient goals for a healthful dietary pattern. Interventions to improve modifiable behaviors might help maintain independence and reduce health care costs. The scalability of successful interventions could be immediate. Because congregate meals represented half of participants’ daily food intake on average, altering menus to reduce foods rich in saturated fat, cholesterol, and sodium while increasing foods rich in protein, calcium, fiber, magnesium, and potassium could help participants achieve dietary recommendations.
Among this sample residing in New York City, most participants met the physical activity recommendation of engaging in 150 minutes per week of moderate physical activity. However, congregate meals centers could serve as a focal point for increasing participation in strength and balance exercises, as these activities reduce the rate of mobility disability (23), and provide non-ambulatory older adults with opportunities to engage in activities that improve functional status.
This work draws upon nationally collected data to characterize the population served and better understand participant perceptions of the program while collecting more detailed nutrition and physical activity information at the local level to inform opportunities for enrichment of existing services that can translate into maintenance of independent living and reduced healthcare costs. Others have examined the diet quality of congregate meal participants on a national (24) and local (5, 6, 25) level. According to 24-hour recall data from 145 congregate meal participants nationwide, program participation was associated with an increase in daily intake of protein by 8 g, fiber by 3 g, calcium by 146 mg, magnesium by 45 mg, potassium by 317 mg, and sodium by 328mg (24). Further efforts to reduce the gap between dietary intake and recommendations would not require drastic intervention measures. For example, incorporating ½ cup of lentils into a meal would add 9 grams of protein, 8 grams of fiber, and 365mg of potassium, and using it as a replacement for sausage would result in a net reduction of 11 grams of fat, 4g of saturated fat, 24 mg of cholesterol and 306 mg of sodium (26).
For the most part, the NYC sample engaged in adequate levels of aerobic activity. Though this was a small sample, the accuracy of these self-reports is supported by an accelerometry study reporting high levels of moderate to vigorous physical activity (MVPA) (39.3 minutes per day using ≥1,041 counts per minute to define MVPA) among 760 NYC residents aged 60 and older (7). Despite aerobic activity, few participated in strength and balance training. Randomized trials have demonstrated the value of strength and balance training on physical function among older adults (27), and large-scale trials are currently underway in Europe testing the effectiveness of multicomponent physical activity interventions (22, 28).  Increasing strength and balance training in community centers might improve overall function and reduce falls.
This work underscores that the prevalence of obesity is high, even among active, older adults who remain socially engaged through activities in community centers. Over half of congregate meals participants in Georgia (53%, n=62) were obese (BMI>=30) (29), while obesity among congregate meals participants residing in New York City residents was 47% (n=467)(5) in Brooklyn and Queens and 36%(n=7) in this small Manhattan sample. Data from this study suggests intervening on the type of foods and activities offered at senior centers could increase the proportion of older adults meeting diet and physical activity recommendations. Furthermore, national survey data supports the popularity of a program that costs less than $11 per meal,(30), and the local data identified opportunities for enhancing services at a local level.
This sample was limited to active participants of congregate meals programs, so we cannot generalize findings to the broader population of older adults.  The convenience sampling strategy likely attracted a subset of senior center participants that were more interested in healthy eating and exercise, so future studies should build upon this work by engaging a more representative sample. As a cross-sectional study, we could not measure future benefits of program participation.  A clinical trial could formally test the effectiveness of diet and physical activity interventions on functional status in a community based setting.


Funding: This study was funded by an Center for Translational Studies Institute award by the Department of Medicine (PI, Beasley). 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: The authors appreciate the contributions of New York City’s Department for the Aging and local community centers and staff to this work.
Conflict of Interest: All authors declare no conflict of interest.



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1. Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA; 2. Department of Scientific and Clinical Affairs, Medifast, Inc., Baltimore, MD, 21202, USA; 3. Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC 27109, USA.
Corresponding author: Barbara J. Nicklas, Ph.D.  Section on Gerontology and Geriatric Medicine, Department of Internal Medicine,  Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC    27157, USA,  Phone: (336) 713-8569,  Fax: (336) 713-8588, e-mail: bnicklas@wakehealth.edu

J Frailty Aging 2018;in press
Published online July 5, 2018, http://dx.doi.org/10.14283/jfa.2018.17



Background: While intentional weight loss in older adults with obesity yields clinically important health benefits there is a need to minimize the negative effects of weight loss on concomitant loss of muscle mass and strength. Data show wearing weighted vests during exercise improves lean mass and lower extremity strength, however the efficacy of wearing a weighted vest during a period of weight loss to mitigate muscle and strength loss is not known. Objectives:  This study examined the feasibility of daily weighted vest use during a dietary weight loss intervention, and examined effects of vest use on body composition and physical function in well-functioning older adults with obesity. Design:  Randomized, controlled pilot study. Setting:  Wake Forest Baptist Medical Center in Winston-Salem, NC. Participants: 37 older (age=65-79 yrs), obese (BMI=30-40 kg/m2) sedentary men and women. Interventions: 22-week behavioral diet intervention (targeting 10% weight loss, 1100-1300 kcals/day) with (Diet+Vest; n=20) or without (Diet; n=17) weighted vest use (goal of 10 hours/day with weight added weekly according to individual loss of body mass). Measurements: Body composition by dual-energy x-ray absorptiometry and measures of physical function, mobility, and muscle strength/power. Results:  Average weighted vest use was 6.7±2.2 hours/day and the vest-wear goal of 10 hrs/day was achieved for 67±22% of total intervention days. Five participants reported adverse events from wearing the vest (all back pain or soreness). Both groups lost a similar amount of weight (Diet= -11.2±4.4 kg; Diet+Vest = -11.0±6.3 kg; p<0.001), with no differences between groups (p=0.25). Fat mass, lean mass, and % body fat decreased significantly (p<0.0001), with no differences between groups. Compared to Diet+Vest, the Diet intervention resulted in greater decreases in leg power (p<0.02), with no other between group differences in physical function. Conclusion:  This pilot study showed that vest use during dietary weight loss is feasible and safe in well-functioning older adults with obesity. Larger studies are needed to definitively determine whether external replacement of lost weight during caloric restriction may preserve lower extremity muscle strength and power.

Key words: Caloric restriction, weighted vest, body composition, physical function, weight loss.




More than one-third of adults in the U.S. over 60 years of age are considered to be obese (body mass index (BMI) ≥30 kg/m2) (1), setting the stage for an acceleration of age- and obesity-related diseases and disability (2, 3). Both obesity and aging are independent risk factors for metabolic disturbances such as dyslipidemia and insulin resistance (4), and elevated BMI in older adults is strongly associated with poor physical function and development of disability (5).
There is growing evidence that planned and supervised weight loss in older adults with obesity yields clinically important benefits in metabolic and physical function (6, 7). However, since aging is associated with a loss of muscle mass (sarcopenia), and weight loss results in loss of muscle in addition to fat loss, there may also be undesired effects of weight loss in older adults who are already at a heightened risk for sarcopenia and dynapenia (8, 9). Thus, there is a need to minimize the negative effects of weight loss, while enhancing its health advantages (10).
Obesity treatment guidelines recommend a comprehensive lifestyle program involving behavioral counseling, caloric restriction, and physical activity (11). In addition, exercise during weight loss in older adults is highly recommended to counteract the loss of muscle mass during weight loss; however, conventional exercise training often requires expensive equipment and, ideally, safety supervision by trained leaders. Moreover, the exercises performed are not always tolerated or sustained, especially in adults with obesity (12). Thus, there is a need to identify novel strategies that are easily adaptable to the environment in which older adults reside. As such, the purpose of this study was to assess the feasibility of daily use of a weighted vest, and to examine the effects of daily vest use on body composition and physical function in older adults undergoing diet-induced weight loss.



Study Design

This 22-week randomized, controlled pilot study (Clinicaltrials.gov; NCT02239939) assessed the feasibility of daily use of a progressively weighted vest and examined the effects of randomization to daily vest use (Diet + Vest, n=20), compared to no vest use (Diet, n=17) during weight loss in older men and women with obesity.

Participant Eligibility

Participants were recruited and enrolled based on the following criteria: 1) 65–79 yrs; 2) sedentary; 3) BMI of 30-40 kg/m2; 4) nonsmoking (<1 cigarette/d or 4/wk within yr); 5) weight stable (<5% weight change in the past 6 mo); 6) willing and able to consume meal replacement products; 7) without insulin-dependent or uncontrolled diabetes, evidence of clinical depression, cognitive impairment, uncontrolled endocrine/metabolic disease, neurological or hematological disease, fibromyalgia, rheumatoid arthritis, cancer, liver or renal disease, chronic pulmonary disease, uncontrolled hypertension, physical impairment (requiring dependency on a cane or walker, osteoporosis, hip fracture, joint replacement or spinal surgery within the last 6 months, or chronic severe back pain) or any contraindication for weight loss. The study was approved by the Wake Forest School of Medicine Institutional Review Board, and all participants provided written informed consent to participate.
A total of 330 individuals were screened by telephone to assess general eligibility. Of these, 56 were invited for in-person screening visits that involved measuring height and weight, a cognition screen (Montreal Cognitive Assessment), physical activity assessment (Physical Activity for the Elderly questionnaire (13)) to insure a sedentary lifestyle, and, if still eligible, a medical history, blood pressure check, and a review of medications. Qualifying participants (n=41) then completed a 3-day run-in period during which they were asked to wear the vest with no weights added, to consume the Medifast® meal replacement products used in the weight loss intervention, and to complete a food record. Four participants withdrew consent during the run-in. Thus, a total of 37 participants met all inclusion and exclusion criteria and were tested on study outcomes before being randomly assigned to an intervention group.


Dietary weight loss intervention

All participants underwent a dietary weight-loss intervention, without a formal exercise program. Caloric deficit was achieved through a combination of meal replacements (MR), conventional foods, and weekly group nutrition/behavioral counseling sessions led by a Registered Dietitian (RD). Participants were instructed to follow the Medifast® 4 & 2 & 1 Plan®, estimated to provide 1100-1300 calories per day.  This meal plan includes a total of 4 MR products, with the addition of 2 lean and green meals and 1 healthy snack. The lean and green meals were prepared by the participants and each consisted of 5-7 oz. lean protein, 3 servings of non-starchy vegetables and up to 2 servings of healthy fat. The healthy snack consisted of one serving of fruit, dairy, or grain. The MR from Medifast® each contained 90-110 kcals and 11-15 g protein. The RD guided participants on their food choices and portion sizes and encouraged participants to consume only what was approved as part of the plan. Daily food logs were collected and reviewed weekly by the RD to verify compliance to the dietary intervention. Compliance was calculated by the RD (based on the self-reported food logs) as the percent of total calories consumed daily relative to the estimated number of calories prescribed (~1200). In addition, body weight was measured weekly to ensure participants were losing weight at a rate approximating their prescribed energy deficit.

Weighted vest intervention

Participants randomized to the weighted vest group (Diet+Vest) each received an appropriately sized vest (Hyper Vest PRO®, Austin, TX) for the duration of the intervention. The vest’s fabric and design fits comfortably under clothing, allowing for full range of motion and movement, and full chest expansion without restricting breathing. The vest firmly and evenly distributes the weight inserts over the body’s core; weights come in 1/8th pound increments.
Participants in this group were asked to wear the vest (under their shirts) on a daily basis, progressing to a goal of 10 hrs/day during the most active part of their day. Initially, no extra weight was added to the vest (vest weight alone is ~0.5 kg). The vest weight was then incrementally increased weekly according to each participant’s rate of weight loss. As body mass decreased, the weight of the vest was increased to replace the lost weight, up to a maximum amount of 15% of the participant’s baseline weight. Participants also kept a daily log to record the time worn, vest weight, and any problems related to vest use. Staff monitored and discussed these logs and participants’ vest use during the weekly group sessions.


All assessments were conducted before and after the interventions. Post-intervention testing occurred during the last week of intervention; participants did not wear the vest during testing.

Body composition and circumferences

Height (Heightronic 235D stadiometer, QuickMedical, Issaquah, WA) and body mass (Detecto scale, Detecto, Webb City, MO) were measured without shoes or outer garments. Whole-body fat mass (FM), lean body mass (LM), and percentage of body fat (%FM) were measured using dual-energy X-ray absorptiometry (Delphi QDR; Hologic, Marlborough, MA). All scans were performed and analyzed by a trained and certified technician. Waist (minimal circumference) and hip (maximal gluteal protuberance) were measured in triplicate with a tape measure; average values are reported and waist-to-hip (WHR) ratio was calculated.

Physical function, mobility and strength

The expanded version of the short physical performance battery (ExSPPB) (12) was used to measure lower-extremity function. The ExSPPB consists of 5 repeated chair stands, standing balance (semi- and full-tandem stands and a single leg stand for 30 seconds), a 4-meter walk at usual pace, and a narrow 4-meter walk test of balance (walking at usual pace within lines of tape spaced 20 cm apart). The continuous scoring system ranges from 0 to 4 with higher scores indicative of better performance. Participants also completed a 400-meter walk (as fast as possible), which is a measure of aerobic endurance (14). The timed stair climb task assessed the time it took each participant to ascend a standard flight of stairs (12 steps).
Maximal isokinetic knee extensor strength (in Newton meters (Nm)) was measured with a dynamometer (Biodex Medical Systems Inc., Shirley, NY) with the participant sitting and the hips and knees flexed at 90°. Participants were asked to extend the knee and push as hard as possible against the resistance pad. The best of 3 trials was selected for each leg. Lower extremity muscle power was measured using the Nottingham Power Rig (15). Power was averaged for each leg following five trials at maximal effort.

Statistical analyses

All statistical analyses were performed with SPSS software (version 21). An α level of <0.05 was used to denote significance and all data were analyzed according to randomly assigned group. Baseline descriptive characteristics are reported as mean (±SDs) or frequencies (percentages). Univariate analyses of variance (ANOVAs) were performed to assess between-group differences at baseline. Within-group differences between baseline and follow-up values were determined using a paired t-test. Between-group differences for change values (baseline minus follow-up) were analyzed using ANCOVA with adjustment for baseline age, gender, race and baseline value of the outcome.



Baseline characteristics, retention, and adherence

The mean age of the randomized participants was 70.1 ± 3 years, and mean BMI was 35.3 ± 2.9 kg/m2, with the majority of participants being female and white. Hypertension was the most prevalent comorbidity. No significant group differences were observed for baseline characteristics (Table 1).
Thirty-three of the 37 randomized participants (89%) completed the study (returned for final data collection). Retention of participants was not different between groups (Diet: 88%; Diet+Vest: 90%). Compliance to the diet intervention was high and did not differ between groups (Diet: 100.3 ± 4.5%; Diet+Vest: 96.3 ± 14.6% of prescribed calories). Over the entire intervention, participants in the Diet+Vest group wore the vest for an average of 6.7 ± 2.2 hours/day (range of 2.0-9.9 hrs/day); only four participants wore the vest for an average of less than five hrs/day. The mean weight in the vest over the intervention period was 6.3±2.5 kg or 7.1±3.0% of baseline body weight. Overall, participants reported meeting the vest-wear goal of 10 hrs/day for 67±22% of the total intervention days. Five participants reported adverse events from wearing the vest (all back pain or soreness); two completely stopped wearing the vest (at weeks 19 and 20), two had interrupted vest use for 2-3 weeks during intervention but resumed vest use for the remainder of the study, and the other one was resolved by decreasing the amount of weight in the vest and not adding additional weight past week 11.


Table 1 Baseline demographic characteristics by treatment group

Table 1
Baseline demographic characteristics by treatment group

All data are Mean ± SD or # (%); 1 Self-reported physician diagnosed osteoarthritis; 2 Non-insulin-treated diabetes; There were no significant differences (at P<0.05) between groups by using ANOVA


The participants in the Diet+Vest group completed a Satisfaction Survey to identify their comfort level and difficulty with wearing the vests during their daily life using a Likert Scale (1-5). These results are shown in Table 2, along with participant comments from an open text field regarding overall satisfaction with daily use of the weighted vest. The majority of participants reported at least some discomfort and some difficulty with putting the vest on, but the majority also reported their daily life was not impeded and little to no pain or soreness from the vest use.

Table 2 Participant satisfaction survey results from Diet+Vest group (n=17)

Table 2
Participant satisfaction survey results from Diet+Vest group (n=17)

Participant Comments about Vest Use: “Got to the point if felt good to wear and helped posture”;  “Not as bad as thought, except had back pain flare up”;  “Uncomfortable when vest got heavier”;  “Makes you realize your weight loss”;  “Vest color was appealing/not as taxing as thought”;  “Putting on vest was hardest part”;  “Bought own vest to wear”


Intervention effects on weight and body composition

There were no group differences at baseline for body mass, circumferences, or body composition (Table 3). Both groups experienced similar and significant weight loss (Diet= -11.2±4.4 kg; 11.9% and Diet+Vest= -11.0±6.3 kg; 10.9%; both p<0.001 compared to baseline), with no difference between groups. Waist and hip circumferences significantly decreased in both groups with no difference between groups. WHR did not change in either group. FM, LM and %FM all decreased significantly (p<0.0001) in both groups, with no significant difference between groups.

Table 3 Circumference measures and body composition at baseline and changes with intervention by study group

Table 3
Circumference measures and body composition at baseline and changes with intervention by study group

All values are mean ± SD; BMI, body mass index; Compared to baseline within each group using paired t-test; *P<0.05; †P<0.0001; Between-group differences on the change values were analyzed with an ANCOVA, adjusted for age, gender, race and baseline value.


Intervention effects on physical function

Table 4 shows physical function and muscle strength by treatment group. Within the Diet group, usual gait speed (0.08 ± 0.10 m/sec) and ExSPPB score (0.15 ± 0.16) improved (p<0.05), whereas muscle power in the right (-11.4 ± 20.9 Watta) and left leg (-9.2 ± 15.2 Watts) decreased (p<0.05). Within the Diet+Vest group, usual gait speed improved (0.11 ± 0.10 m/sec; p<0.0001). Compared to Diet+Vest, Diet resulted in greater decreases in left and right leg power (p<0.05). There were no between group differences in the other measures of physical function.

Table 4 Physical function variables at baseline and changes with intervention by study group

Table 4
Physical function variables at baseline and changes with intervention by study group




Results of this study suggest that external replacement of lost weight via daily use of a weighted vest during caloric restriction in well-functioning older adults with obesity is feasible and may have a beneficial impact on health outcomes. Overall, adherence to wearing the vest was good, with average vest wear time of over six hours per day and the daily goal of ten hours of vest use met on 2/3rds of intervention days.  In this small pilot, vest use did not differentially affect decreases in body mass, fat mass or lean mass, but decreases in leg muscle power were attenuated with vest use.
Obesity is a strong predictor of limitations in physical function in older adults (16, 17), and weight loss with exercise results in improved function and mobility in this population (7, 18). In this study, both groups achieved a therapeutic level of weight loss (greater than 10% decrease), moving them close to the overweight BMI range. Weight loss of this magnitude is consistent with that observed in a previous study using meal replacements for weight loss in overweight/obese older adults (19), and is similar to the level of weight loss generally seen in even longer-term (12-18 month) caloric restriction studies in older adults (6, 7).
Even when combined with exercise and higher protein intake, weight loss naturally results in a loss of some muscle mass, in addition to fat loss (9, 20). The loss of muscle during weight loss is partially attributed to the decrease in mechanical stress as weight is reduced (21). Thus, enhancing gravitational load on muscle via weighted vest use during a period of caloric restriction could potentially diminish the amount of muscle lost for a given weight loss (22, 23). In this study, both groups lost a similar and significant amount of both fat and lean mass, with the majority of total weight lost being fat; however, the added mechanical load from the weighted vest did not result in greater preservation of lean mass in this small sample.  This is contrary to findings from animal studies, where mechanisms regulating skeletal tissue structure and function responded in a similar fashion to increases in actual or externally added body mass (21, 24). Previous studies of older adults wearing a weighted vest, but just while exercising, did not examine effects on muscle mass per se (25-27), making it difficult to compare the changes in muscle mass we observed with results from other studies.
Conservation of muscle mass is a particularly important consideration for older adults as the age-related decreases in muscle strength and power are well characterized and associated with decreased functional capacity in this population. Very little research to date examined effects of weight loss on muscle strength and power in older adults (7). In this study, both groups maintained muscle strength, with no differences between groups. On the other hand, the weighted vest prevented declines in leg muscle power, suggesting this may be a safe and effective method for preserving and potentially improving muscle power during weight loss. These results are similar to a prior study by our group, where we found improved leg power, but not knee extensor strength in older women performing resistance training (RT) during caloric restriction compared to caloric restriction without RT (28).
The preservation of lower extremity muscle power we observed in the Diet+Vest group did not transfer into an improvement on power-related functional tasks such as rising from a chair or stair climbing. However, an interesting observation of our results, that is of relevance to the controversy surrounding promoting intentional weight loss in older adults, is that the caloric restriction alone (i.e. without a structured exercise regimen) which resulted in significant reductions in body mass and lean mass, did not negatively affect key measures of physical function, including chair rise time, global score of physical function (ExSPPB), stair climb time, or 400-meter walk time. In fact, both groups experienced significant improvements in usual gait speed, and the Diet group significantly improved ExSPPB scores. It should also be noted that the adults who volunteered for this study were all relatively high-functioning at baseline and it is not known whether similar results would be found in those with impaired function.
The results of this study need to be interpreted within the context that it was an exploratory pilot study with a relatively small number of participants who were well-functioning at baseline. However, the study provided important insights into the feasibility, practicality and compliance of using a weighted vest during a dietary weight loss intervention in older adults. While, on average, compliance to vest use was good, one-fourth of the participants in this group reported additional back pain and had to disrupt vest use or limit the amount of weight added. Future studies will need to examine the risk:benefit ratio of weighted vest use in this population of older adults with obesity.
In summary, diet-induced weight loss, with or without daily weighted vest use, produced significant decreases in body weight, fat and lean mass, without impacting physical function in older adults with obesity. Further, use of the vest during weight loss was feasible and safe and appears to help preserve lower extremity muscle power. The implication of these findings are that countering the decreased mechanical load with weight loss by externally replacing lost weight appears to be a promising approach to counteract some aging and obesity-associated conditions; however, future studies using a larger sample size are needed to confirm these findings.


Funding: This work was supported by the Arthritis and Musculoskeletal Disease Research Center; Translational Science Center; and Center for Integrated Medicine at Wake Forest School of Medicine. These sponsors had no role in the design and conduct of the study, in the collection, analysis, and interpretation of data, or in the preparation of the manuscript.  An in-kind product donation was made by Jason Pharmaceuticals, Inc., a wholly owned subsidiary of Medifast, Inc.
Conflict of Interest: The researchers do not hold a direct financial interest in the sponsors or the product being studied.



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1. University of Utah, College of Health, Dept of Physical Therapy and Athletic Training, Salt Lake City, UT, USA; 2. George Fox University, Dept of Physical Therapy, Newberg, OR, USA
Corresponding author: Dr Robert A. Briggs, David Grant USAF Medical Center, 101 Bodin Circle, Travis AFB CA, 94535, USA; Phone: 208-520-6884; FAX: (707) 423-5242;
email: robert.a.briggs.mil@mail.mil

J Frailty Aging 2018;7(1):51-56
Published online August 30, 2017, http://dx.doi.org/10.14283/jfa.2017.31



Background: Muscle mass deficits endure after hip fracture. Strategies to improve muscle quality may improve mobility and physical function. It is unknown whether training after usual care yields muscle quality gains after hip fracture. Objectives: To determine whether muscle quality improves after hip fracture with high-intensity resistance training and protein supplementation. Design: Case series. Setting: University of Utah Skeletal Muscle Exercise Research Facility. Participants: 17 community-dwelling older adults, 3.6+/-1.1 months post-hip fracture, recently discharged from usual-care physical therapy (mean age 77.0+/-12.0 years, 12 female), enrolled. Intervention: Participants underwent 12 weeks (3x/week) of unilaterally-biased resistance training. Methods/Materials: Participants were measured via a 3.0 Tesla whole-body MR imager for muscle lean and intramuscular adipose tissue (IMAT) of the quadriceps before and after resistance training. Peak isometric knee extension force output was measured with an isokinetic dynamometer. Muscle quality was calculated by dividing peak isometric knee extension force (N) by quadriceps lean muscle mass (cm2). In addition, common physical function variables were measured before and after training. Results: Surgical and nonsurgical lean quadriceps muscle mass improved among participants (mean change: 2.9 cm2+/-1.4 cm2, and 2.7 cm2+/-1.3 cm2, respectively), while IMAT remained unchanged. Peak force improved in the surgical limb by 43.1+/-23N, with no significant change in the nonsurgical limb. Significant gains in physical function were evident after training. Conclusion: Participants recovering from hip fracture demonstrated improvements in muscle mass, muscle strength, and muscle quality in the surgical limb after hip fracture. These were in addition to gains made in the first months after fracture with traditional care. Future studies should determine the impact that muscle quality has on long-term functional recovery in this population.

Key words: Muscle quality, hip fracture, physical function



Hip fracture is a devastating event for many older adults, with 25% not surviving the year following fracture, and incomplete recovery of prefracture mobility in 60% of survivors (1). Approximately 1.6 million older adults worldwide sustain a hip fracture annually, with estimates approaching 4.5 million annually by 2050 (2) Management of older adults following hip fracture has become a large-scale healthcare and societal issue. Identifying novel strategies to improve physical function in this vulnerable population is necessary.
Older adults after hip fracture experience a “catabolic crisis,” that often prevents full recovery (3). Compared to the gradual muscle loss typical of aging (i.e., sarcopenia), acute changes in body composition are evident following hip fracture. Older women typically gain 1.7% of fat mass and lose 1% of lean mass per year with aging (4). However, a 6% decline in lean muscle mass, and up to 11% increase in fat mass is evident in the first year after hip fracture (5). The majority of the body composition changes evident at 1 year after fracture occur in the first 60 days, with 90% of the full body muscle mass loss observed in the lower extremities, specifically the quadriceps (6).
Rapid muscle loss accompanying hip fracture increases risk of long-term mobility and physical function deficits. As little as 5 days of bed rest contributes to a 4% decrease in leg lean muscle mass and a 16% reduction in knee extension strength in otherwise healthy older adults (7). Recent studies suggest that older adults exhibit poor muscle recovery following disuse-related muscle loss (8). Lower lean mass and declining strength in the legs, particularly in the surgical limb quadriceps, are linked to poor mobility and muscle function (9). Unfortunately, muscular deficiencies in the surgical limb seem recalcitrant for years after the initial trauma and accompanying surgical intervention following hip fracture (10). In combination, adverse effects on muscle composition are associated with increased disability, recurrent fracture, and mortality (9).
Muscle quality, defined as muscle force per unit of muscle cross-sectional area (11), is emerging as a salient contributor to physical function in older adults, particularly among frail, older women (12). Misic et al. have implicated muscle quality as the strongest independent predictor of lower extremity function among older adults, explaining up to 42% of the variance in physical function (13). Besides predicting physical performance, muscle quality is associated with gait variability (14), mobility impairments, self-reported physical function limitations, and disability (15). In light of ample recent evidence, researchers agree that lower extremity muscle quality is independently associated with physical function (11-15). Thus, in addition to efforts to mitigate losses in muscle mass and muscle strength, recovery of muscle quality may be a critical target to prevent declines in physical function in older adults following hip fracture. Muscle quality rates of decline are cited as 11-13% among community-dwelling older men and women over a 5 year span (11). The rate at which muscle quality declines or returns following rehabilitation among older adults after hip fracture is unknown.
The purpose of this study was to describe changes in muscle quality and its components (i.e., force and lean mass) in response to an extended high-intensity training regime implemented 3 to 6 months after hip fracture. Secondarily we describe the changes in physical function after extended rehabilitation. We hypothesized significant improvements in muscle quality would occur following training, which would accompany physical function gains.




Seventeen community-dwelling older adults recovering from hip fracture, and recently discharged from 8-12 weeks of usual-care physical therapy, participated in the study. Each had incurred a hip fracture in the past 3 to 6 months (mean = 3.6 ± 1.1 months), and had been discharged from physical therapy (mean = 2.4 ± 1.3 weeks).
Participants were recruited from two hospital systems between December 2013 and February 2015. Inclusion criteria were a unilateral hip fracture in the past 6 months, functionally independent, community-dwelling, and completion of usual-care physical therapy (acute, subacute, and/or home health interventions). Individuals were excluded based on significant osteoarthritis (taking regular medications for joint pain), obvious lower extremity range of motion impairments, and various known medical conditions, (e.g., neurological, cardiovascular, respiratory diseases, etc.) likely to interfere with their ability to effectively participate in high-intensity resistance training. Comorbidities in this relatively healthy older cohort were few, with the most common comorbidities in this sample being: regulated high blood pressure, diabetes, low-grade inflammation, temporary urinary tract or lung infection, sinus congestion, and mild depression. During the trial 3 participants complained of occasional knee pain, 2 missed at least one session due to urinary tract infection, and 1 missed three sessions of training due to lung infection. Participants were screened via the Montreal Cognitive Assessment (MoCA), requiring a score greater than 23/30 on the MoCA (mean = 27.9 ± 1.8) to demonstrate cognitive competence to provide informed consent.

Thigh Muscle Composition, Muscle Strength and Muscle Quality

Magnetic resonance imaging (MRI) determined CSA of lean muscle mass and intramuscular adipose tissue (IMAT). Bilateral scans of the thighs were obtained and subjects were placed supine in a 3.0 Tesla whole body MR imager (Siemens Trio, Siemens Medical, Erlangen, Germany). The legs were scanned in a coronal plane and the midpoint of the thigh was determined and defined as halfway between the superior margin of the femoral head and the inferior margin of the femoral condyles. Axial imaging (5mm thick slices at 1 cm intervals) of the legs was then performed over 1/2 the length of the femur, centered at the midpoint of the thigh. Separate fat and water images were created with custom software using the three-point Dixon method (16). Five images from the middle 1/3 of each thigh were used to determine average CSA (cm2) of IMAT and lean tissue. (Figure 1) Manual tracing eliminated subcutaneous fat and bone and isolated the fascial border of the thigh to create a subfascial region of interest (ROI). Total IMAT and lean tissue were calculated within the ROI using custom-written image analysis software (MATLAB; The MathWorks, Natick, Massachusetts). This sum was multiplied by the area of each pixel to give total fat and lean tissue CSAs within the ROI and respective IMAT and lean tissue CSAs were calculated after excluding subcutaneous fat and bone (16). The same investigator, blinded to time point of the scan and slice location, performed measurements of individual participants before and after training. Intra-investigator reliability of this technique in our laboratory is excellent (mean ICC=0.99) and has been previously published (17).

Figure 1 Representative Baseline MR Images of Right and Left Thigh

Figure 1
Representative Baseline MR Images of Right and Left Thigh

Pre-training MRI demonstrates significant atrophy of the surgical (right) thigh musculature.


An isokinetic dynamometer (KinCom, Chattanooga Inc, USA) was used to determine unilateral knee extension strength. Participants were positioned with their hip at 90 and knee at 60 degrees of flexion. A maximal voluntary isometric contraction (MVIC) of the knee extensors over a 3-second duration was recorded. The average MVIC of three trials (with 30-second rest between trials) was used for analysis. This method has excellent reliability (0.81-0.98).
Muscle quality was calculated by dividing peak isometric knee extension force (N) by quadriceps lean mass (cm2).

Physical Function

Physical function was assessed with a battery of tests to document physical performance among older adults. The Six Minute Walk (6MW) test is a reliable performance-based measure of locomotor ability, and endurance (18). The Timed Up-and-Go (TUG) test assesses mobility among older adults, with scores > 13.5 seconds predictive of fall risk (19). The Stair Climb Test (SCT) and Stair Descent Test (SDT) are valid, simple, clinically relevant measures assessing functional decline in community-dwelling older adults (20). The five times sit-to-stand (5xSTS) is a reliable, valid measure of lower extremity strength and power (21). The 14-item Berg Balance Scale (BBS) provides a reliable and valid measure of static balance, and predicts fall risk (22).
The 29-item Lower Extremity Measure (LEM) is a reliable, valid self-report questionnaire described to identify frailty (23). The 16-item Activities-Specific Balance Confidence scale is a validated, reliable, self-report of balance confidence, that is associated with mobility, balance performance, and perceived postfracture mobility limitations (24).


A 3-month, unilaterally biased, high-intensity resistance training program, emphasizing improvements in surgical limb muscle function, whole-body balance, and confidence was incorporated in this study. Participants attended three 60-80-minute supervised exercise sessions per week over a 12-week duration. The group sessions included a warm-up, six lower extremity strength exercises (3×8 repetitions at 85% of the surgical limb 1-RM), balance/mobility exercises, sit-to-stand repetitions, gait training, and lower extremity eccentric ergometer resistance training (Eccentron, BTE Tech, Hanover, MD). Following each exercise session, participants consumed a protein-rich drink (17g whey protein (4.6g Leucine); BCAA Pepform BCAA Peptide, Glanbia Nutritionals, Twin Falls, ID) intending to maximize muscle mass and strength gains by enhancing the adaptive physiological response to resistance training (25, 26). 1-RM values were measured and recorded after the initial 3 weeks training, then retested every 3 weeks to maximize resistance training stimuli. Depending on specific exercise, individuals improved an average of 40%-65% in 1-RM over the 12-weeks training, comparable to gains documented after a similar postfracture resistance training trial (27).

Data Analysis

Descriptive data were calculated for demographic and clinical variables and are presented as means ± SD. Means and 95% CIs of the primary outcome variables for comparison of differences between pre- and posttraining were tested with paired-sample t-tests. Effect sizes were calculated for body composition and physical function changes observed with training. Statistical analysis was completed using SPSS 22.0 (Armonk, NY), significance set at p ≤ 0.05.



Baseline Characteristics

Demographic and descriptive characteristics at baseline for the sample are presented in Table 1. The sample was representative of a typical community-dwelling, post-hip fracture population. Clinical measures, including usual gait speed of 0.9 m/s ± 0.3m/s, TUG of 12.5s ± 5.4s, and LEM of 74.7 ± 9.8 describe older adults who, though functionally independent, presented with continued mobility impairments, and moderate fall risk after usual-care.

Table 1 Descriptive Characteristics of Study Sample

Table 1
Descriptive Characteristics of Study Sample

All measures refer to baseline measurement. Means ± Standard Deviation. Yr = year, mos = months, ORIF = open reduction internal fixation, hemi = hemiarthroplasty, THA = total hip arthroplasty, MoCA = Montreal Cognitive Assessment, m/s = meters/second, LEM = Lower Extremity Measure, s = seconds, N = Newtons

Thigh Muscle Composition, Muscle Strength and Muscle Quality

The surgical limb lean quadriceps muscle mass was significantly smaller (36. 3 cm2 ± 11.1 cm2 vs. 41.8 cm2 ± 13.5 cm2 p < 0.001), significantly weaker (251.9N ± 131.0N vs. 333.9N ± 131.0N p < 0.001) and had lower muscle quality (6.8 ± 2.4 vs. 7.7 ± 1.9 p < 0.05) than the nonsurgical limb at baseline. There was no significant difference between surgical limb and nonsurgical limb IMAT at baseline (p = 0.57).
The surgical limb quadriceps muscle mass increased significantly with training (mean change = 2.9 cm2, p < 0.001) with an average lean mass gain of 9%. Muscle mass gain in the nonsurgical limb also increased with training (mean change = 2.7 cm2, p = 0.001) with an average lean mass gain of 7%. Knee extension strength increased significantly in the surgical limb with training (mean change = 43.1N, p = 0.001) for an average strength gain of 21%. Knee extension strength did not change significantly in the nonsurgical limb (p=0.46). Muscle quality improved significantly in the surgical limb with training (mean change = 0.5, p < 0.05) for an average gain of 14%. Muscle quality decreased in the nonsurgical limb (mean change = 0.6, p < 0.05). Quadriceps IMAT did not change significantly in either limb, while percent fat decreased significantly (p < 0.05) in both the surgical and nonsurgical limbs (Table 2).


Table 2 Changes in Muscle Composition and Muscle Quality Components with Training

Table 2
Changes in Muscle Composition and Muscle Quality Components with Training

Bold* = changes significant, p < 0.05, Bold** = changes significant, p < 0.001. Pre-/Post-Training changes listed as Means ± Standard Deviation; Quad = quadriceps muscle, IMAT = Intramuscular Adipose Tissue, N = Newtons.


Physical Function

All measures of physical function improved significantly with training (p < 0.005) and improvements exceeded clinically meaningful differences (CMDs) for all clinical measures in which CMD have been established (Table 3). Depending on the measure, observed clinical performance improved by an average of 10% – 30% yielding moderate to large effect sizes ranging from 0.50 to 0.98.

Table 3 Means Pre-/Post-Training Physical Function Variables

Table 3
Means Pre-/Post-Training Physical Function Variables

All functional measures improved significantly with training (p<0.05). Pre-/Post-Training changes listed as Means ± Standard Deviation. 6MW = Six Minute Walk, GS = gait speed, TUG = Timed Up-and-Go, SCT = Stair Climb Test, SDT = Stair Descent Test, 5xSTS = 5 x sit-to-stand, BBS = Berg Balance Scale, LEM = Lower Extremity Measure, ABC = Activities-Specific Balance Confidence. N/A indicates no established clinically meaningful difference value for the specified performance measure.



Significant deficits in muscle mass and muscle quality remain apparent 8-12 weeks after hip fracture among community-dwelling older adults following usual-care physical therapy. Similar to previous reports, strength was significantly less in the surgical limb than the nonsurgical limb despite having undergone several weeks of usual-care rehabilitation (10, 27, 28). Additionally, we identified sizable muscle mass and muscle quality deficits in the surgical limb (10-15%) compared to the nonsurgical limb after usual-care. This finding indicates that acute declines in muscle mass and muscle quality in the surgical limb remain evident after usual-care, but can be significantly improved with extended high-intensity rehabilitation. While muscle mass remained significantly lower in the surgical limb; muscle quality improved, eliminating the between-limb muscle quality discrepancy following resistance training.
Our results confirm previous reports suggesting that significant, clinically meaningful gains in strength and function are expected after extended high-intensity resistance training (28). The fact that these improvements were accompanied by improved muscle mass in the quadriceps region is encouraging since a significant amount of lean tissue is lost after hip fracture, especially in the lower extremities (6), and muscle mass recovery after inactivity in older adults is often diminished (8).
Despite improved muscle mass, nonsurgical limb strength did not change. While unexpected, neural activation may partially explain the significant strength gains noted in the surgical limb and lack of strength improvement in the non-surgical limb. A recent study identified a 10% decrease in activation in the lower limb of older adults, but not younger adults, after 2 weeks of limb immobilization (8); while resistance training has been shown to improve activation and muscle size among older adults after elective hip replacement surgery (29). The surgical limb is inactive relative to the nonsurgical limb, thus improved neural activation combined with improvements in muscle mass likely contributed to increased isometric strength in the surgical limb. Because participants relied more on their nonsurgical limbs for mobility since fracture, the opportunity for increased neural activation following the intervention was less in the non-surgical limb. Thus, improvements in muscle mass alone may not have been sufficient to induce significant improvements in nonsurgical limb strength. We did not quantify, thus cannot confirm the contribution of neural activation to isometric strength in this sample.
Lean mass gains observed in this study may have been amplified by the addition of the leucine-enriched protein supplementation (25). The ~5g leucine provided to participants following each exercise session might have served as an important rehabilitation adjunct to maximize muscle gains in this vulnerable population. Malnutrition is common among older adults admitted to the hospital with hip fracture, and most do not meet the recommended daily allowance (RDA) for protein (0.8 g/kg body weight/day) (30). This accentuates the need for preserving mass and mitigating weight loss, particularly among the frail, since this subpopulation is most at risk for functional losses, yet least likely to receive robust resistance training. Though we do not know the direct effect of the protein supplement, we suppose that it augmented muscle composition and strength gains (26), and should be considered in future strategies to mitigate postfracture muscle mass loss.
These results should be taken in light of some limitations. Participants were generally cognitively and physically healthy, motivated, community-dwelling elderly participants recovering from hip fracture who volunteered for a regimented exercise program. Whether these results are generalizable to older adults with additional impairments is unknown. We observed an average improvement of 14% in muscle quality in the surgical limb following training among participants who were used as their own controls. Therefore we are unable to attribute our findings to the intervention alone.



Despite having completed usual-care physical therapy, significant impairments in muscle quality and its components remain evident after hip fracture. Extended high-intensity resistance training following usual care after hip fracture improves muscle strength and physical function. Our results suggest that muscle mass and muscle quality deficits identified in the surgical limb can be reversed with training. Future studies should determine the impact of muscle quality gains on long-term functional recovery and quality of life in this population.


Acknowledgements: I would like to acknowledge the university students who devoted countless hours to this intervention study. Two students in particular should be mentioned for their dedication to this project. Brad Powell spent many hours assisting with participant training, manpower assistance recruiting, transportation scheduling, and imaging analysis. Ally Armstrong devoted countless hours to the MR imaging data collection, compilation, and analysis. Gerrard Brennan is also appreciated for assistance with recruitment of participants from Intermountain Healthcare.
Author Contributions: RAB provided study concept and design, collected, analyzed, and interpreted data, and wrote the manuscript. PCL provided study concept and design, consultation, and manuscript editing. JRH provided study concept and design, assisted with analysis and interpretation, and reviewed the manuscript. JMF provided consultation and manuscript editing. MJD provided consultation, assisted with recruitment, and manuscript writing and review. RLM provided study concept and design, data analysis and interpretation, manuscript editing, laboratory and analytical tools, and supervised the study.
Financial Disclosure and Conflict of Interest. One of the authors (PCL) is a co-inventor on the ergometer licensed to Eccentron; BTE Technologies, Inc., Hanover, MD, USA. Neither PCL nor any of the other authors have received any financial incentives (e.g., reimbursements, fees, royalties, funding, or salary) from the company or stemming from the contents of this manuscript or any related published papers. There are no other potential conflict of interest declared by the authors.
Study approval: Institutional Review Board University of Utah IRB_00062639, Intermountain Healthcare Institutional Review Board IRB_1040261.
Ethical standard: We have read and have abided by the statement of ethical standards for manuscripts submitted to Journal of Frailty and Aging, and are compliant with legal and ethical standards of human research.



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1. Physiotherapy Research Group, Department of Global Public Health and Primary Care, University of Bergen, Norway; 2. Department of Clinical Medicine, University of Bergen, Norway; 3. Department of Neuroscience, Faculty of Medicine, Norwegian University of Science and Technology, Norway;      
Corresponding author: Bård Bogen, University of Bergen, Postbox 7804, N-5018 Bergen, Norway, E-mail: bard.bogen@uib.no, Telephone: +4791157142

J Frailty Aging 2017;6(2):88-90
Published online April 19, 2017, http://dx.doi.org/10.14283/jfa.2017.11



Abstract: Many older people do not participate in organized exercise, and daily walking may be the most substantial contributor to physical activity. To investigate the association between daily walking behavior and self-reported health-related physical function, older community-dwelling volunteers wore activity-registering sensors for three days. Self-reported health-related physical functioning was measured using the SF36 10-item Physical Function subscale. Forty-six participants wore a sensor (mean age 77.6, SD 3.6, 61 % women). In a multiple regression model, steps per day (B=.005, p≤.001) and walks per day (B=-.174, p=.010) were associated with the SF36-PF subscale. The association between physical functioning and walks per day was negative: Those who took many walks per day may have been walking more indoors. Health professionals are likely justified in advising older people to incorporate walking into daily life for health purposes. The cross-sectional design does not allow for inferences about causality.

Key words: Walking, older adults, physical function.




Many older people do not exercise (1), and walking in daily life situations may be the greatest contributor to their physical activity (2). Walking at least 7500 steps per day has been suggested as sufficient to meet recommendations of daily physical activity (3, 4). Many studies have investigated walking behavior using self-report, which may be prone to both over- and underestimations (5).  Use of small, body-worn, unobtrusive sensors that allow for multi-day continuous recording of movements has become more widespread, providing direct information about walking behavior in the wearer’s own surroundings. The association between objectively measured walking behavior and health and functioning has not been studied extensively. We hypothesized that volume and intensity in walking behavior is associated with having few health-related functional limitations. To investigate this, we assessed the association between three days of free-living walking behavior, and health-related physical functioning.



Study design and participants

A cross-sectional design was used, with randomly selected volunteers, between 70-81 years old and one third male. Participants were invited by mail and telephone and those who were able to walk 10 meters independently and able to give an informed consent, were included. The study was approved by the Regional Ethics Committee (No. 2010/1621)

Daily walking

Daily walking was assessed by use of ActivPALTM activity monitors (PAL Technologies Ltd, Glasgow, UK), (53*35*7 mm, 20 g, 20Hz). Participants wore the accelerometer on the front of the thigh, attached by a gel pad that was adhesive on both sides. The ActivPAL was waterproofed to allow for showering, however, the participants were asked not to go swimming or bathing. The monitors detect lying/sitting and standing positions, transitions between positions, and steps. ActivPALs have been shown to have high accuracy for step detection at different speeds and under different conditions (6, 7). In this study, data from three consecutive days are used for analysis. Time spent walking per day, walks per day and steps per day are believed to reflect volume of walking, while longest walk during the three days of recording and steps per walk reflect intensity of walking.

Physical function

The 10-item physical function subscale from the SF36-questionnaire is a measure of limitations in mobility and physical functioning due to health problems. It includes 10 questions concerning limitations in vigorous activity, moderate intensity activity, lifting/carrying a shopping basket, squatting/bending, walking, stair ascending and bathing/dressing (“How much does your health prevent you from…?”). A score of 100 indicates no limitations in either of the items and a score of zero indicates serious limitations in all items. The SF36 10-item physical function subscale (SF36-PF) has been described as a valid measure of mobility disability (8).

Data analysis

Activity monitoring data was analysed by use of software version 7.1.18 from PAL Technologies Ltd. A custom-made MATLAB program (MATLAB version 7.1, The MathWorks Inc., Natick, MA, 2005) derived event information about walking.

Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics 20 and Microsoft Excel 2010 for Windows. Age, daily walking variables and the SF36-PF subscale are presented as means and standard deviations. To explore which of the daily walking variables that had closest association with the SF36-PF subscale, we used multiple regression with a backwards method, entering all daily walking variables simultaneously, with only variables with p-values ≤.10 remaining in the final model. In the same model, we adjusted for age and gender by including these using forced entry. In the results, unstandardized coefficients, standardized coefficients, p-value and explained variance (R2) are presented. The variance inflation factor (VIF) was inspected for assessment of collinearity.



Data was available for 46 individuals (61% women). The mean age was 77.3 (SD 3.6) years. Participants’ descriptive details are shown in Table 1.


Table 1 Descriptive statistics for daily walking variables and physical function (n=46, mean age 77.6, SD 3.6)

Table 1
Descriptive statistics for daily walking variables and physical function (n=46, mean age 77.6, SD 3.6)


BMI: body mass index; SF36-PF: SF36 questionnaire Physical Function; SD: standard deviation; range: minimum-maximum value

Before performing a multivariate analysis, bivariate correlations between all variables were inspected. The association between walking time per day and steps per day was very high (r=.933, p≤.001). As these variables would essentially convey the same information, time per day was not used in further analyses. In a multiple regression model with age and gender entered using a fixed method and daily walking variables entered using a backwards method, and the SF36-PF subscale as the dependent variable, steps per day and walks per day remained in the final model, with positive and negative associations respectively. In addition, being female was negatively associated with the SF36-PF subscale. There was no significant interaction between the two daily walking variables that remained in the final model (steps per day*walks per day). The explained variance for the final model was .37. When removing the variable “walks per day” explained variance was .27, while removing the variable “steps per day” gave an explained variance of .12, suggesting that steps per day had most explanatory power in the model (Table 2). Steps per day and walks per day and longest walk had VIF-values above 8.1 in the initial model, suggesting collinearity between these variables. VIF-values in the final model were found to be less than 1.4, giving no concern for collinearity.

Table 2 Multiple regression model with gender and age (fixed method) and daily walking variables (backwards method) as independent variables, and the SF36 PF subscale as dependent variable

Table 2
Multiple regression model with gender and age (fixed method) and daily walking variables (backwards method) as independent variables, and the SF36 PF subscale as dependent variable



In this study, we have investigated daily walking behavior and self-reported physical functioning in older community-dwelling people. In a multiple regression analysis, steps per day and walks per day were significantly associated with the SF36-PF subscale, positively and negatively respectively.
Daily number of steps is a widely reported measure. On average, the participants in our study walked approximately 7300 steps per day, which may be characterized as being “low active”. 54% walked less than 7500 steps per day, which is lower than the equivalence of 30 daily minutes of moderate to vigorous physical activity (4).
There was a negative association between number of walks and the SF36-PF subscale, suggesting that participants who took many walks per day experienced more difficulties in physical functioning than those who took few walks. One possible interpretation is that those who took many walks stayed indoors more: Outdoor walking generally requires walking over longer distances, while being indoors allowstasks to be completed with relatively fewer steps per walk. Restrictions in life-space mobility are associated with low physical functioning, and movement through more life-space areas is associated with higher physical activity (9). The questions in the SF36-PF are also to some degree directed towards outdoor mobility.
The variables longest walk and steps per walk were not retained in the multiple regression model. As the questions in the SF36-PF subscale are directed primarily towards volume (distance), and not intensity of walking, this is perhaps unsurprising. In another study, longest walk was associated with fewer falls; however, the participants were older and had dementia and cannot be directly compared to the participants in our study (10). The participants may have used cars or public transport for mobility, or for other reasons chosen not to walk more than they did on the days of recording. There may be a clear distinction between what persons are capable of doing (when tested in the laboratory) and what they actually choose do (during free living).
Explained variance in the regression model was modest, suggesting that other factors not measured here also play important roles. Limitations of this study include sample size, a potential observer effect and the cross-sectional design that does not allow for inferences about causality. Also, we did not control for season or weather in the analysis, which may affect the inclination to venture outside (11). In addition, non-walking physical activity was not measured.
In this study of daily life walking in community-dwelling older people, we show that steps per day was positively associated with health-related physical functioning. Health professionals are likely justified in advising older people to walk for health-purposes.


Funding: This study was funded by grants from The Norwegian Fund for Post-Graduate Training in Physiotherapy and The Kavli Research Center for Geriatrics and Dementia. The funders 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.
Conflict of Interest: None of the authors report any conflict of interest.



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Department of Agin and Geriatric Research, University of Florida College of Medicine, Gainesville, FL, USA

Corresponding author: Thomas W. Buford, Department of Aging and Geriatric Research, University of Florida, Gainesville, FL 32611, Telephone: 352-273-5918, Fax: 352-273-5920, Email: tbuford@ufl.edu



The purpose of this review was to evaluate randomized controlled trials aiming to preserve the functional status, i.e. physical capabilities, of middle-aged and older cancer survivors through a structured, physical exercise intervention. The study team performed a thorough search of the literature using six online databases. This literature search limited included studies to randomized controlled trials which implemented a structured physical activity intervention for middle- and older-aged adults diagnosed with cancer. Studies were also required include at least one objective measure of physical function as a dependent outcome. This literature search yielded thirty-eight studies. The majority of the literature reviewed was successful in improving several functional outcomes including time needed to rise from a chair or distance covered during the six-minute walk test. A large number of published trials also suggest that exercise is effective in decreasing fatigue. However, a lack of trials investigating outcomes in older populations (≥ 65 years) was noted in this review. The results of this review suggest that a structured exercise program may be physically beneficial for middle-aged to older cancer survivors. Particularly, such interventions could preserve the functional status of cancer patients and, consequently, improve their long-term health outcomes. Future implications include further investigation into strictly older cancer patient populations, as outcomes related to exercise might differ between older and middle-aged adults.


Key words: Exercise, exercise therapy, cancer treatment, physical function, cancer survivor.



Functional status, determined by measures of physical performance, is an important predictor of health outcomes in older adults. The capacity to perform basic physical functions is a central aspect of health-related quality of life (1) and a key predictor of hospitalization, surgical outcomes, and mortality (2, 3). Accordingly, maintenance of independent functioning is a critical factor in preserving the health and well-being of older adults. In the U.S., nearly half of the 37.3 million persons aged ≥ 65 years report having one or more physical limitations in performing essential daily tasks (4). The adverse outcomes associated with these limitations have created a significant burden on healthcare systems, which is likely to become more substantial given that older adults represent the fastest growing segment of the population (5). As a result, the development of methods to maintain the health and independence of older persons is an important public health goal. 

Numerous co-morbid conditions contribute to the progression of functional decline among older adults; cancer being among the most prevalent and most debilitating. Over 60% of the 14.5 million cancer survivors in the U.S. are over 65 years of age, and the number of older cancer survivors is expected to increase by nearly 30% in the next decade. The monumental healthcare costs ($37-48 billion) associated with treatment of older cancer survivors are expected to increase similarly. Notably, the financial and human costs of cancer survivorship continue long past diagnoses and initial treatment (6, 7). Yet evidence-based treatments which address the complex long-term medical needs of older cancer survivors are lacking (6, 7). Consequently, the development of efficacious interventions to enhance the long-term health and wellness of older cancer survivors is an important research goal with public health implications.

To date, physical exercise is currently the only intervention consistently demonstrated to attenuate functional decline among older adults. However, many cancer survivors face unique challenges (e.g. depression, fatigue, cognitive decline) which may limit the extent of functional improvement in response to physical exercise. These challenges may be particularly acute among patients who have undergone treatment with radiation and/or chemotherapy. The objective of this manuscript was to therefore review the available literature related to studies of exercise for preservation of functional status in late life. Notably, prior reviews have evaluated the efficacy of exercise for improving quality of life outcomes and the physical function of all-age cancer patients (8, 9). However, to our knowledge, this would be the first review of the literature related to the use of physical exercise in the preservation of functional status among older cancer survivors.



Literature Search

A thorough literature search was conducted using literature available through the University of Florida Online Library, PubMed, MEDLINE, NIH Reporter, the Cochrane Library, and Web of Science. We conducted these searches using the following search keywords: exercise therapy/exercise treatment/physical activity/exercise/cancer treatment/intervention/physical function AND cancer/androgen suppression therapy/chemotherapy/cancer survivor. The goal of this literature search was to collect publications that will improve the understanding of older cancer patients’ responses to physical exercise interventions. Specifically, the efficacy of such interventions in preserving the physical function of these individuals was the main focus of our search. The included literature was limited to randomized controlled trials which involved a structured physical activity intervention – e.g. aerobic training, strength training, etc. – and incorporated at least one objective measure of physical function (e.g. 6-Minute-Walk-Test, timed up and go, etc.).  Initial searches focused on older adults (i.e. > 65 years of age), however our search was later broadened to include middle-aged adults (> 45 years) given the relative scarcity of trials for older cancer survivors. The scope of the search was then further narrowed to focus on prostate, breast, and mixed tumor types, as little relevant literature exists outside of these designations. Mixed tumor types were defined as controlled trials in which the study cohorts were composed of patients with varying cancer types. Furthermore, trials addressing exercise treatment in conjunction with palliative care were excluded as palliative care was outside the scope of this review. 



Study Characteristics

A review of the literature provided 38 studies that met our requirements for inclusion (10-47). All studies were controlled trials that lasted between 21 days and 18 months in duration and were published between 1989 and 2015.  These studies overwhelmingly included dependent outcomes related to functional fitness, physiologic predictors of function, and exercise behavior. Of those reviewed, 20 studies examined the effectiveness of exercise interventions during treatment for cancer (10, 12, 14, 17-21, 23-27, 30, 31, 43-47) and 18 studies include post-treatment participants or cancer survivors (11, 13, 15, 16, 22, 28, 29, 32-42). The studies were categorized based on type of cancer as well as completion of treatment, and the resultant categories include prostate cancer, breast cancer during treatment, breast cancer after treatment, and mixed tumors. These categories represent the four areas in which the majority of the literature is available.  

In total, 3,398 individuals participated in the studies reviewed. A significant portion of these participants came from the RENEW trial (N=641), which makes up nearly 20% of the individuals in this review. The exercise modalities reviewed and deemed safe for aging cancer patients and survivors include aerobic exercise (10-14, 16-24, 26, 28-30, 33-45, 47), resistance exercise (11-14, 17, 19, 21, 22, 24-27, 29, 32-35, 37-42, 45), qigong classes (which include elements of Tai Chi) (15), Nia exercise (a combination of martial arts, yoga, and dance) (31), Greek traditional dance classes (32), and soccer training (46). Aerobic and resistance interventions were either home-based or center-based and were performed at varying levels of intensities across studies. Two studies included separate aerobic and resistance interventions (17, 26). Reference group activities included standard care (10-14, 16-18, 20, 23, 26, 28-33, 35-37, 40, 43-47) stretching classes (15, 21), wait-list controls (19, 25), relaxation (27), physiotherapy (24), psychotherapy (34), delayed exercise (22), or home-based exercise (39). We assessed outcome variables for each study, but we did not evaluate subjective measures such as quality of life and pain given prior reviews on these topics (8, 9). 

Prostate Cancer

A total of 738 prostate cancer patients, 598 actively undergoing treatment, participated in nine trials ranging from N= 21 to N = 155 (14, 15, 19, 23, 25, 26, 39, 45, 46).The mean age of participants in these studies was 69.2 years old, with all studies having a mean age > 65 years old. Individuals undergoing treatment had been prescribed androgen suppression/deprivation therapy (14, 19, 25, 45, 46), or radiation therapy (23, 26). Two studies were composed of prostate cancer survivors not actively undergoing treatment, and these individuals were classified as older, fatigued, and sedentary (15, 39). Trial durations ranged from eight weeks to twelve months. All prostate studies are represented in Table 1. 


Table 1 Prostate Cancer

*Functional fitness assessed as the maximum number of repetitions of a standardized chair sit-to-stand test; †Muscle strength was measured by an eight repetition maximum of horizontal bench press and leg extension; ‡Denotes resistance intervention outcome §Denotes aerobic intervention outcome;  Population values are Mean ± Standard Deviation (SD) or Mean ± SD Exercise Group; SD Control Group in cases which cohort SD was not reported; Median and/or range were included in population values if mean and/or SD were not reported; + indicates a statistically significant increase in the variable in response to the exercise intervention;  – indicates a statistically significant decrease in the variable in response to the exercise intervention; 0 indicates no statistically significant relationship found; VO2 max: Peak Oxygen Consumption; BMI: Body Mass Index


Three trials employed combined aerobic and resistance exercise interventions (14, 19, 39). Two of these trials measured aerobic capacity through a 400 meter walk test[39] or a six-minute walk test (19). Intervention groups significantly improved in 400 meter walk test times and in walking distance compared to a home-based exercise control. These trials also reported that the combined intervention did not change fatigue for the exercise group compared to a control. One trial measured lower body performance via a timed chair rise time test, and a twice-weekly supervised aerobic and resistance home-based exercise program significantly decreased chair rise with a mediation effect of 1.7 (0.6 to 4.5) compared to a standard care control (39). A separate study assessed functional fitness as the maximum number of chair sit-to-stand repetitions, and the 12-week aerobic and resistance exercise lifestyle program increased in the exercise group by 3.66 repetitions compared to the standard care control. This intervention also significantly decreased participant fatigue – as measured by Functional Assessment of Cancer Therapy-Fatigue scores – by 3.1 points compared to the control (14).   

Two trials implemented strictly aerobic interventions (23, 26). These assessed aerobic capacity by submaximal aerobic capacity measures (23) or peak oxygen consumption (VO2 max) (26). The 24-week aerobic intervention increased exercise group VO2 max by 1.4 ml/kg/min, and the 8-week aerobic intervention increased exercise group submaximal aerobic capacity by 2.8 metabolic equivalents. Both were compared to standard care controls. The 8-week aerobic intervention also measured lower body strength with a timed, five-repetition chair sit-and-stand test. Participants in the tri-weekly aerobic exercise intervention had between-group comparison pre- to post-radiotherapy score decreases of 1.7 ± 0.9 in the time taken to complete the five repetitions compared to the standard care control (23). An additional two trials employed resistance exercise interventions (25, 26). Both trials measured upper- and lower-body strength using eight-repetition maximum tests for bench press and leg press. For lower body muscular fitness, leg press repetitions increased by 11.8 in the intervention group and decreased by 1.6 in the control group (25). Lower- and upper-body strength were superior with resistance training (P<.001 for both) when compared to a control and aerobic training (26). Additionally, both trials decreased fatigue levels compared to controls. 

A soccer training intervention for patients undergoing androgen deprivation therapy measured VO2 max, lean body mass, knee-extensor strength, and percent body fat (46). The trial improved lean body mass and improved muscle strength for knee extensors (1RM) in the intervention group (P < 0.001). Sit-to-stand repetitions increased significantly compared to a control with a mean change score of 1.4. However, the intervention was unable to significantly change VO2 max compared to the control. An intervention employing qigong classes (exercise that incorporates meditation and Chinese martial arts) for fatigued and sedentary survivors was able to increase fatigue assessment scores (higher score=less fatigued) – as measured by the Functional Assessment Chronic Illness Therapy-Fatigue Scale (scale 0-52) – for exercise participants by 5 points compared to a stretching class (15). A home-based diet and exercise intervention for prostate cancer patients measured fatigue and aerobic capacity by a six-minute walk test. The intervention increased exercise group six-minute walk test scores by 36.5 meters compared to a standard care control. No significant change was seen with fatigue (45). 

Breast Cancer during Treatment 

A total of ten exercise intervention studies exist which included individuals with breast cancer actively undergoing chemotherapy or radiation therapy (10, 17, 20, 21, 27, 30, 31, 43, 44, 47). The studies ranged in sample sizes from N=14 to N=242 individuals, and in total the ten studies were comprised of 740 participants. The mean age of individuals in these trials was 50.3 years old, with no studies focusing on older breast cancer survivors (> 65 years). These studies included a combined aerobic-resistance intervention (21), aerobic interventions (10, 17, 20, 30, 43, 44, 47), resistance training (17, 27), and a Nia exercise program (31). All breast cancer during treatment studies are represented in Table 2. 


Table 2 Breast Cancer During Treatment

*Denotes resistance intervention outcome; † Denotes aerobic intervention outcome; ‡Muscle strength was measured by an eight repetition maximum of horizontal bench press and leg extension; §Short-Form 36 Health Status Survey Measuring Physical Function; | |Muscle strength was measured for isometric and isokinetic muscle capacity of upper and lower extremity muscle groups; Population values are Mean ± Standard Deviation (SD) or Mean ± SD Exercise Group; SD Control Group in cases which cohort SD was not reported; Median and/or range were included in population values if mean and/or SD were not reported; + indicates a statistically significant increase in the variable in response to the exercise intervention;  – indicates a statistically significant decrease in the variable in response to the exercise intervention ; 0 indicates no statistically significant relationship found VO2 max: Peak Oxygen Consumption   


One study assigned participants to either an aerobic or resistance intervention and assessed aerobic capacity, fatigue, and muscle strength. Aerobic capacity was measured by peak oxygen consumption, and the intervention increased VO2 max by approximately 8% for the aerobic exercise group compared to a usual care control. For the resistance exercise group, the resistance intervention was able to increase eight repetition maximums for leg and chest press by approximately 30% compared to the usual care control. Fatigue, as measured by the Functional Assessment of Cancer Therapy-Anemia scale, did not change significantly for either exercise group compared to the control (17). A separate trial employed a five-week, combined aerobic and resistance exercise for stage I-III breast cancer patients. Fatigue was assessed via the brief fatigue inventory questionnaire (scale 0-10), and the intervention was able to significantly decrease (p<0.05) scores for the exercise group compared to a stretching control (21). 

A total of six studies employed a home-based or center-based aerobic exercise intervention (10, 20, 30, 43, 44, 47).Four of these measured aerobic capacity or physical function through peak oxygen consumption (VO2 max) (10, 20) or submaximal aerobic capacity measures (43, 44). Trials that assessed VO2 max had conflicting results. A 16-week, aerobic intervention was unable to significantly change peak oxygen consumption measurements for the exercise group compared to a control (10). However, a 12-week, aerobic intervention was able to increase VO2 max by 21.9% for the exercise group compared to a standard care control (20). A 26-week, home-based aerobic intervention was able to increase participants measures of submaximal aerobic capacity by 2.4% compared to a standard care control (44). An aerobic interventions also showed success in decreasing the exercise groups’ fatigue levels (30). One trail measured physical function through the Short-Form 36 Health Status Survey, and the 26-week, home-based aerobic intervention was able to increase scores for the exercise group by 9.8 points compared to a standard care control (44). 

One study examined the effects of a twelve-week, progressive resistance training intervention (27). Muscle strength was measured through muscle capacity of upper and lower extremities, and the intervention was able to increase isokinetic and isometric muscle strength (p<0.0001) compared to a relaxation control. Aerobic capacity was assessed by peak oxygen consumption, but no significant change was found for the exercise group compared to the control. Numerical group differences and changes were not reported for muscle strength and aerobic capacity. This trial also measured fatigue through the Fatigue Assessment Questionnaire (scale 0-10), and the intervention was able to decrease the exercise group’s scores by 0.5 points compared to the relaxation control. 

A Nia exercise program was employed in a group of breast cancer patients undergoing radiation therapy (31). Nia exercise combines forms of yoga, dancing, and martial arts as a comprehensive exercise approach. This trial measured cardiovascular fitness through a six-minute walk test, but the intervention did not significantly change distance walked between the exercise and control group. The trial also assessed fatigue through the Functional Assessment Chronic Illness Therapy-Fatigue Scale (scale 0-160). The Nia exercise intervention increased fatigue scores (higher score=less fatigue) for the intervention group by 7.1% compared to the standard care control.  

Breast Cancer after Treatment 

Studies in the breast cancer after treatment group included individuals who were assigned to an exercise intervention after completion of treatment for breast cancer. Nine studies (11, 16, 22, 28, 29, 32, 33, 35, 36) totaling 384 participants ranged in length from 6 weeks to 18 months and sample sizes N=14 to N=104. The mean age of these breast cancer patients was 55.6 years old, with no studies focusing on older survivors. Exercise interventions included aerobic exercise, (16, 28) combined aerobic and resistance exercise, (11, 22, 29, 33, 35) a home-based moderate physical activity program, (36) and a combined Greek traditional dance and resistance program (32). Control groups included standard care (11, 16, 28, 29, 32, 33, 35, 36) and a delayed exercise group that completed the exercise intervention after a 12-week waiting period (22). All breast cancer after treatment studies are represented in Table 3. 


Table 3 Breast Cancer after Treatment

* Short-Form 36 Health Status Survey Measuring Physical Function; †Muscle Strength measured by recording weight used for bicep curls, leg presses, and chest extensions; Population values are Mean ± Standard Deviation (SD) or Mean ± SD Exercise Group; SD Control Group in cases which cohort SD was not reported; Median and/or range were included in population values if mean and/or SD were not reported; + Indicates a statistically significant increase in the variable in response to the exercise intervention;  – Indicates a statistically significant decrease in the variable in response to the exercise intervention; 0 Indicates no statistically significant relationship found; VO2 max: Peak Oxygen Consumption; BMI: Body Mass Index


Studies that employed a combined aerobic and resistance intervention assessed aerobic capacity through a six-minute walk test, (11, 35) VO2 max, (29) and submaximal aerobic capacity measures (22). All four of these combined interventions reported increases in participant’s measurement of aerobic capacity at the commencement of the trials compared to standard care controls. Muscle strength was assessed by either leg extension strength (35) or by recording weight used for bicep curls, leg presses, and chest extensions(22). Measurements of leg extension strength increased by an average of 25.4 newtons in the combined exercise group compared to a standard care control. The recorded weight used for bicep curls, leg presses, and chest extensions increased by an average of 71% for the combined intervention group compared to a standard care control. One study assessed physical function through the Short-Form 36 Health Status Survey, but did not show a significant change in participant’s scores by the end of the intervention compared to a standard care control (33).  

Two total studies used strictly aerobic exercise interventions (16, 28). Both assessed aerobic capacity through VO2 max. A fifteen-week aerobic intervention reported a 14.4% increase in peak oxygen consumption for the exercise group compared to a standard care control (28). However, a 12-week, moderate-intensity aerobic intervention reported no significant change in peak oxygen for the exercise group compared to a standard care control (16). A six-week home-based, moderate physical activity intervention reported an increase in six-minute walk test measurements with the exercise group walking an average of 97 feet farther in six minutes compared to a standard care control (36). 

An intervention that combined resistance exercise with a Greek traditional dance course measured physical function through a six-minute walk test score, while also assessing handgrip strength (32). Six-minute walk test scores increased by an average of 55.21 meters in the exercise group compared to a standard care control. Handgrip strength was assessed using a baseline handheld dynamometer, and the exercise group averaged a 21% increase in strength compared to the control at the end of the trial.  

Mixed Tumors

Ten studies enrolled a total of 1,536 participants with mixed tumor types and ranged from 21 days to 12 weeks in duration.(12, 13, 18, 24, 34, 37, 38, 40-42) The mean age of these participants was 59.8 years old, with four studies having a mean age > 65 years. Sample sizes ranged from N=18 to N=641. The exercise interventions implemented in these studies included aerobic exercise, (18, 40) combined resistance and aerobic exercise, (12, 13, 24, 37) and home-based exercise.(34, 38, 41, 42) Controls were standard care, (12, 13, 18, 37, 40) standard physiotherapy, (24) or psychotherapy (34). All mixed tumor studies are represented in Table 4.


Table 4 Mixed Tumors

*Measured by one repetition maximum of leg press, chest press, and pull down; †Short-Form 36 Health Status Survey Measuring Physical Function/Functional Decline; ‡Type of testing not reported; §Measured via the basic and advanced lower extremity function subscales of the Late Life Function and Disability Index.; | |Functional Assessment of Cancer Therapy-Anemia measuring patient-reported physical function ; Population values are Mean ± Standard Deviation (SD) or Mean ± SD Exercise Group; SD Control Group in cases which cohort SD was not reported; Median and/or range were included in population values if mean and/or SD were not reported; + Indicates a statistically significant increase in the variable in response to the exercise intervention ; – Indicates a statistically significant decrease in the variable in response to the exercise intervention ; 0 Indicates no statistically significant relationship found  ; VO2 max: Peak Oxygen Consumption; BMI: Body Mass Index


Two trials implemented aerobic exercise interventions (18, 40). A ten-week, light to moderate aerobic intervention assessed aerobic capacity though submaximal oxygen consumption measures. The intervention increased submaximal aerobic capacity in the intervention by 15.9% compared to a standard care control (40). Additionally, a twelve-week, aerobic exercise intervention increased VO2 max by 43% in the exercise group compared to a usual care control. This trial also assessed physical function and fatigue through FACT-Anemia scores subscales of function and fatigue. The aerobic intervention increased mean intervention group physical function scores by 7.2 points (scale of 0-188) and increased mean fatigue scores by 4 points (scale 0-52; higher score=less fatigue) compared to the standard care control (18). 

A total of four studies employed a combined aerobic and resistance exercise program (12, 13, 24, 37). All of these trials measured muscle strength through upper/lower body strength, (12) quad muscle strength, (13) and abdominal muscle strength (24). Exact measurements of muscle strength for the Starting Again trial-a breast, ovarian, testicular, and prostate cancer group rehabilitation program-were not reported (37). A six-week, high intensity resistance and aerobic intervention reported an average 29.6% weight improvement for one-repetition maximums for the exercise group compared to a standard care control (12). A four-week, combined intervention assessed quad muscle strength, but reported no significant change in strength for the intervention compared to a standard care control (13). 

Two combined aerobic and resistance interventions assessed aerobic capacity through measures of VO2 max. A three-week, combined intervention reported a 24.4% increase for the intervention group compared to a standard physiotherapy control (24). A six-week, high intensity resistance and aerobic intervention reported an average 10.7% increase in VO2 max for the intervention group compared to a standard care control. This trial also assessed physical function through Short-Form 36 Health Status Surveys (SF-36), and fatigue through the European Organization for Treatment and Research of Cancer Quality of Life Questionnaire. The study reported an average 2.2 SF-36 score increase and an average 6.6 QLQ-C30 score decrease for the intervention compared to the control (12). 

Three studies examining the RENEW trial, a large home-based exercise intervention for older, overweight cancer survivors, attempted to assess physical function, functional decline, and lower extremity function (38, 41, 42). All trials measured physical function or rates of functional decline through SF-36 score measures. One intervention assessing the rate of functional decline decreased SF-36 scores by 2.3% for the exercise group. However, SF-36 scores decreased by 7.8% for the control group that did not receive the exercise intervention (41). A separate trial also found similar results, as the intervention decreased SF-36 scores by 2.15 points for the exercise group, but individuals of the control group experienced a decline of 4.84 points at the end of the trial. Lower extremity function scores were assessed via the basic and advanced lower extremity function subscales of the Late Life Function and Disability Index. The intervention increased scores slightly (0.34 points), while control group participants showed a decreased of 1.89 points (42). Lastly, a trial distinguished physical function and lower extremity function between high-to-light physical activity (HLPA), moderate-to-vigorous physical activity (MVPA), and low-to-light physical activity (LLPA) groups. Survivors who increased HLPA and decreased or stabilized MVPA, scored 3.04 points higher on SF-36 scales and 2.28 points higher on basic lower extremity function scales compared to survivors who decreased MVPA or maintained stable MVPA and HLPA (38).



The objective of the present review was to evaluate the extant literature related to the use of physical exercise for improving functional status among middle-aged and older cancer survivors. To our knowledge, this is the first review specifically focused on the use of exercise to maintain physical function among middle-aged and older cancer survivors. The results of this review suggest that these patients may physically benefit from exercise during and after cancer treatment as the majority of published trials demonstrated reasonable efficacy of exercise in improving functional status among these populations. Notably, there are several ongoing trials that should be monitored closely so their results can be compared to the findings of this review (48-50).

Among the various cancer groups highlighted in this review, prostate and mixed tumor groups had by far the highest number of studies focusing on older cancer patients. The majority of these various interventions showed success in lowering rates of functional decline and improving objective measures of physical function for these aging populations. These results are consistent with other trials that have implemented exercise as a form treatment for geriatric patients suffering from other diseases known to accelerate functional decline. For instance, studies examining the effects of physical activity on older individuals suffering from cardiovascular disease have shown that exercise is capable of attenuating age-related decline caused by hypertension or heart failure (51). Similar results have been shown in elderly populations diagnosed with osteoporosis, as exercise has proved successful in increasing bone density and improving other physical outcomes for these patients (52). Overall, it is encouraging that the results of interventions for those suffering from cancer, a separate disease widely known to negatively impact physical function, are comparable with other trials showing improvement for aging populations. 

With the benefits of exercise interventions as a form of cancer treatment for middle-aged to older adults becoming more tangible, it is imperative that future trials study populations strictly made up of older adults. As stated previously, this review saw a significant gap in the literature for exercise in only older patient populations (≥ 65 years old). It is paramount that more of these studies examine this population because of the dramatic clinical costs of functional decline and the rapidly growing population of older adults. It may also be important to evaluate the efficacy of creative interventions designed to facilitate adherence among these populations. Examples of such interventions may include the use of dancing, yoga, or interactive video games. For instance, one ongoing study is examining the efficacy of video game exercise interventions on a group of older breast cancer survivors (53). It is possible that cancer patients might perceive these nontraditional exercise interventions as less strenuous, potentially leading to higher motivation and commitment to the regimens. These types of interventions, specifically dancing, may also attenuate cognitive decline- an independent predictor of functional decline among older adults and common side effect of chemotherapy (54-56). Prior studies of the general geriatric population have demonstrated cognitive-motor benefits from both dancing and traditional exercise performed with music (57, 58). 

Like any study, there were some limitations to this review. First, not every study in this review used blinding methods (blinding of outcome assessor, blinding of care provider, etc.), and several studies (10, 19, 20, 23, 28, 32, 33, 35, 40, 43, 47) had very small samples sizes. Additionally, the exercise modalities, durations, and disease stages were not all standardized across the reviewed trials, which may have led to variance among outcome measurements. However, all studies did utilize supervised intervention programs and employed parallel comparison control groups. Also, the availability of substantial literature regarding prostate and breast cancer was a positive given that these two forms of cancer are by far the most prevalent among older adults (59). 

To conclude, the role of exercise interventions in attenuating functional decline in cancer patients offers some very positive implications. This review found that cancer-related fatigue could be lowered through resistance or aerobic exercise in multiple cancer types. This is likely a very important effect for the patient given that reduced fatigue can greatly influence the functional status of cancer patients (60). Additionally, the ability of interventions to increase the aerobic capacity and muscle strength of individuals can point towards improvements in their diagnoses. Amelioration of all these physical outcomes could lead to lower patient morbidity and mortality rates. However, those implementing exercise in a clinical setting should be wary of patient’s responses to varying intensities and modalities of the interventions. In summary, the results of this review suggest that the use of exercise as a form of cancer treatment may be vital for maintaining and improving the physical health of middle-aged and older cancer survivors. 


Funding: No direct funding was used for this manuscript.

Acknowledgements: This work was partially supported by the University of Florida Claude D. Pepper Older Americans Independence Center, funded through the National Institutes of Health (P30AG028740).

Conflicting Interest: None.



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1. Department of Clinical and Experimental Medicine- Section of Internal Medicine, Gerontology, and Geriatrics – University of Ferrara, Italy; 2. Division of Geriatric, Department of Medicine, St. Anna Hospital, Ferrara, Italy; 3. Department of Neurology, Division of Special Neurology, Medical University of Graz, Graz, Austria; 4. Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland.

Corresponding Author: Stefano Volpato, MD, MPH, Department of Clinical and Experimental Medicine, University of Ferrara, Via Savonarola, 9, I-44100 Ferrara, ITALY, e-mail vlt@unife.it, phone +39-0532-247409, FAX +39-0532-210884

J Frailty Aging 2012;1(1):32-38
Published online February 14, 2012, http://dx.doi.org/10.14283/jfa.2012.6


Objectives: Objective measures of physical function are useful prognostic tools also for hospitalized elders. Low handgrip strength is predictive of poor outcomes and it can be assessed also in a sitting position, representing a potential alternative measure in bedridden patients. We evaluated grip strength prognostic value in hospitalized older patients. Design: Prospective cohort study. Setting: Geriatric, medical ward of an academic medical center in Ferrara, Italy. Participants: Patients aged 65 and older (N = 88) admitted to the hospital for an acute medical condition. Measurements: Patients were evaluated for grip strength at hospital admission and were re-evaluated at discharge. After discharge, they were followed every 3 months for 1 year by telephone interviews to assess new hospitalizations and vital status. Results: The mean age of the sample was 77.3 years, 47% were women. At admission, mean height standardized handgrip strength was 15.7±5 kg/m; men had greater strength (p<0.001). There was a direct relationship of admission grip strength with BMI (p<0.05), serum albumin (p=0.07), and Short Physical Performance Battery score (p<0.05), and an inverse relationship with age (gender-adjusted p value <0.01). In multiple regression analysis, after adjustment for possible confounders, patients in third tertile of grip strength had a shorter hospital stay compared to those in the first tertile (β -2.8; p<0.05). Patients with higher grip strength at discharge also had a lower risk of rehospitalization or death over the follow-up, although the result was not statistically significant (OR: 0.68; 95% CI: 0.30-1.52). Conclusion: In older hospitalized medical patients, grip strength assessment might provide useful prognostic information.

Key words: propecia long term results strength, physical function, hospitalized elders.



In older patients, assessment of functional status is fundamental to determine the appropriate care strategy and to evaluate patient’s clinical course over time (1). Indeed, functional status evaluation is likely to simultaneously capture the integrated and multisystemic effects of aging, affective and cognitive disorders, comorbidity, and disease severity on the health status of older persons. Self-reported and objective measures of physical function can provide independent and complementary information both among community-dwelling older patients and among geriatric acute care medical inpatients (2).

Previous studies from our and other groups, showed that objective measures of lower extremity performance, including gait speed and balance tests, are valid and reliable prognostic tools also for hospitalized elders. For example, we have recently demonstrated that the Short Physical Performance Battery (SPPB) score (3) is independently associated with the length of hospital stay and that SPPB score assessed at hospital discharge identifies patients at higher risk for re-hospitalization or death over the following 12 months (4, 5). Nevertheless, not all hospitalized geriatric patients are able to stand up and walk, narrowing SPPB clinical application in the acute care setting. Handgrip strength, that can be assessed in a sitting or supine position, might represent a potential useful alternative objective evaluation tool in acutely ill patients.

Handgrip strength correlates with the strength of other muscular groups (6), it is considered a good indicator of the neuromuscular system status, is inversely related to age (7) and is influenced both by genetic and environmental factors (8, 9). Data from the Honolulu-Asia Aging Study showed that handgrip strength assessed in healthy middle-aged subjects could predict the risk of functional limitations 25 years later (10). Some studies demonstrated that low handgrip strength is correlated with higher risk of mobility disability (11), cognitive decline (12), and with the risk of hospitalization and other poor outcomes (13, 14). In the Women’s Health and Aging Study it has been proved that lower handgrip strength is a powerful predictor of all-cause, cardiovascular, and respiratory-related mortality (15). Moreover Rantanen et colleagues suggested that handgrip strength could be considered an index of body resilience to the aging process (16). Nevertheless the prognostic value of grip strength assessment in the acute care setting has not been investigated so far.

The aim of this study was therefore to evaluate the clinical correlates and to assess the short- and long-term predictive value of handgrip strength in a sample of acutely ill older inpatients enrolled in a 1-year observational study.


Study design and data collection

Between October 1, 2004 and December 31, 2006, patients, admitted to the academic center of Internal Medicine and Geriatrics (University of Ferrara, Italy), were screened for eligibility for a 1-year longitudinal observational study, as previously described (4). Briefly, inclusion criteria for the study were as follows: (a) age 65 years and older; (b) ability to stand and walk for a few meters at the time of study enrollment; (c) a clinical diagnosis of one of the following conditions: congestive heart failure, chronic obstructive pulmonary disease (COPD), pneumonia, and minor stroke. Patients were considered ineligible for the study if they had severe cognitive impairment (Mini-Mental State Examination score <18), acute coronary syndrome, if they were living more than 25 km (15.5 miles) from the medical center, or if they refused to participate in the study. The local institutional review board reviewed and approved the study protocol. Of those eligible, 92 (74%) agreed to participate, signed the informed consent, and were enrolled in the study. Participants were evaluated by three trained research physicians by means of a comprehensive geriatric assessment at hospital admission, were re-evaluated the day of hospital discharge, then 1 month after hospital discharge by in-home visits, and subsequently, every 3 months by telephone interviews. The performance-based measures of physical function were assessed at hospital admission, within 24 hours before hospital discharge, and during the home visit 1 month after hospital discharge. Four patients without grip assessment at hospital admission were excluded form this analysis leaving a sample of 88 patients.



Socio-demographic information, including gender, marital status, living arrangement, educational level, and smoking habits were collected at baseline by standardized interview.

Performance-based measures of physical function

Performance-based measures of physical function included the SPPB and handgrip strength. Trained research physicians tested all performance-based measures. Handgrip strength was measured using a JAMAR hand dynamometer (Model BK-7498, Fred Sammons Inc., Brookfield, IL) following a standardized protocol: patients were in a seated position with the elbow flexed at 90° and were encouraged to exhibit the best possible force. Assessment of handgrip strength was repeated three times for each hand and the best measure in the stronger arm was chosen (15) and standardized for height. The assessment of grip strength using a handheld dynamometer has been previously shown to be reliable and valid among hospitalized older patients (17, 18).

The SPPB includes usual walking speed over 4 meters, time to complete five chair stands as quickly as possible and three hierarchical balance tests. A score (scale, 0–4) for each task was assigned and a summary performance score was created for each participant (range 0–12) summing the three individual categorical scores, with higher scores indicating better lower body function (4). The SPPB score is a global measure of lower extremity functioning that predicts mobility loss, nursing home placement, and mortality among community-dwelling elderly individuals and it has been shown to be reliable, valid, and sensitive to change (19).

Self-report measure of physical function

Information on six instrumental activities of daily living (IADL) was obtained using a modified version of the Lawton and Brody scale. The six activities included were as follows: using the telephone, travelling via car or public transportation, shopping, housecleaning, handling money, and taking medications. Participants were asked if they had any difficulty performing each task without help from another person or special equipment. If they said they did have difficulty, they were then asked how much difficulty, with response options of ‘‘some difficulty, a lot of difficulty, or unable to do without help.’’ At hospital admission the patients were asked if they had any difficulty performing each task during the preceding 2 weeks. Disability in basic ADL (BADL) was measured according to the participants’ self-reported difficulty in performing each of six activities: getting in and out of a bed, bathing, dressing, eating, personal hygiene, and using the toilet. For BADLs the format was the same used for IADLs. Based on the results of previous work (20, 21) showing a high rate of decline in ADL function in the weeks preceding hospital admission, information on ADL was queried for both hospital admission and during the preceding 2 weeks.

Cognitive and affective function

Cognitive functioning was assessed using the MMSE (22). Patients with scores of ≤24 were considered to have mild cognitive impairment. Depressive symptoms were measured using the Center for Epidemiological Studies–Depression (CES-D) Scale (23) (range from 0 to 60, with higher scores indicating more depressive symptomatology). Patients with scores >16 were considered to have depressive symptomatology (24).

Comorbidity and indicators of disease severity

Comorbidity was assessed by using the Cumulative Illness Rating Scale (CIRS) a validated physician-rated index derived by means of patient history as well as physical examination and laboratory findings (25). The CIRS is divided into 14 categories or disorders. This index measures the chronic medical illness burden while taking into consideration the severity of chronic diseases. The final score of the CIRS is the sum of each of the 14 individual system scores, with higher values indicating greater disease burden severity. The CIRS Comorbidity Index 1 (26) (CIRS CM1) takes into account the number of categories with a score of 1 or greater, including psychiatric.

Statistical Analysis

After standardization for height (Kg/m), grip strength was analyzed as continuous variable and as a three-level ordinal variable, according to sex-specific tertiles (men: 17.0 and 21 kg/m; women: 11.5 and 13.5 kg/m). The association with clinical and self-reported functional characteristics was evaluated across sex-specific tertiles of grip strength by using analysis of variance and chi-square test for continuous and categorical variables, respectively. The short-term prognostic value of handgrip strength for predicting hospital length of stay, a proxy measure of health status and length of recovery (27), was assessed as a function of grip strength evaluated at hospital admission. This analysis was performed using multivariable linear regression models adjusting for age, gender, cognitive status, comorbidity, basic ADL disability, because these demographics and clinical characteristics are major determinants of clinical course in elder hospitalized patients. In addition in order to investigate if the prognostic value of grip strength, was independent of other performance measure the analysis was also adjusted for SBBP score. The long-term grip strength prognostic value was evaluated predicting the incidence of a composite outcome, in which new hospitalizations and death were combined, in the twelve months following hospital discharge. Discrete-time survival analysis with logistic regression was used to estimate the association between handgrip strength, assessed at hospital discharge, and the likelihood of new hospitalization or death. Each participant potentially contributed an observation for each 3-months follow-up interval (for a maximum of 4). In fact, each patient contributed data up to the round at which he/she first reported a new hospitalization, died or was lost to follow-up and not evaluated thereafter (censored). Logistic models were adjusted for demographic characteristics, cognitive status, comorbidity, and BADL summary scale score 2 weeks before hospital. All analyses were performed using STATA statistical software (release 11; College Station, TX).


The study sample consisted of 88 patients; the mean age was 77.3 years (range 65-93), 47% were female. Main admission diagnoses were congestive heart failure (62.5%), COPD (17%), pneumonia (13.6%), and minor stroke (6.8%). Handgrip strength at hospital admission ranged from 5.7 to 27.1 kg/m with a mean value of 15.7 ± 5.1 kg/m. As expected men were stronger than women, with men having greater grip strength (18.7 ± 4.6 kg/m vs 12.5 ± 3.3 kg/m, p<0.001). For both men and women grip strength did not change substantially during hospital stay, although women tended to have higher strength at hospital discharge (Figure 1).

Figure 1 Handgrip strength distribution at hospital admission and discharge in men and women

Patients with greater handgrip strength were more likely to be younger, to have higher BMI, higher levels of serum albumin and had a better SPPB score. They were also less likely to need caregiver assistance (Table 1). Stronger patients were more likely to have prevalent diabetes and hypertension. There was no association of handgrip strength with other demographics, clinical and functional variables.

Table 1 Main clinical and functional characteristics at baseline by sex-specific tertiles of handgrip strength

* Men cut-offs are: 1st tertile 7.3-16.9 kg/m; 2nd tertile 17.0-20.6 kg/m; 3rd tertile 21.7-27.0 kg/m. Women cut-offs are: 1st tertile 5.7-11.5 kg/m; 2nd tertile 11.5-13.4 kg/m; 3rd tertile 13.6-21.9 kg/m. ** CM1= Charlson Comorbidity Index, calculated as the number of categories with a score of 1 or greater, including psychiatric.

Table 2 displays multiple linear regression models predicting length of hospital stay according to handgrip strength. After adjustment for age and gender, patients belonging to the highest strength tertile showed a shorter length of hospital stay compared to patients in the lowest tertile (with a difference of approximately 3 days, p=0.022). Results were substantially unchanged after full adjustment, including cognitive status, BADL disability 2 weeks before hospital admission, BADL disability at hospital stay, and level of comorbidity (Model 2) (p=0.011). Including SPPB tertiles in the fully adjusted model also (Model 3) there was a minimal reduction in the difference between the highest and lowest tertiles and the estimate remained statistically significant (-2.82 days for higher tertile, p=0.046). Analyzing handgrip strength as continuous variable and adjusting for possible confounders, a 1 kg/m increase of strength was associated with a 0.4-day reduction in hospital stay (p=0.004). In other words, a 5 kg increase in strength was associated with a 1.9 days reduction in hospital stay for a woman of 1.56 m height (average height) and 0.9 days for the average height man (1.7 m). The relationship between grip strength and length of hospital stay was consistent in both men and women.

Table 2 Multiple linear regression models predicting length of hospital stay according to grip strength in men and women

Model 1: adjusted for age and gender; Model 2: adjusted for age, gender, BMI, MMSE score, BADL 2 weeks before hospital admission, CIRS total score; Model 3: adjusted for age, gender, BMI, MMSE score, BADL 2 weeks before hospital admission, CIRS total score,  SPPB score tertiles. *For lower tertile, the adjusted means (SE) are: Model 1 [10.40 (1.05)]; Model 2 [10.37 (1.07)]; Model 3 [11.50 (1.36)]. **For lower tertile, the adjusted means (SE) are: Model 1 [10.48 (1.20)]; Model 2 [10.75 (1.25)]; Model 3 [12.59 (1.52)]. ***For lower tertile, the adjusted means (SE) are: Model 1 [11.80 (1.28)]; Model 2 [12.25 (1.31)]; Model 3 [12.68 (2.00)].

In Table 3 are shown the odds ratios for rehospitalization or death according to handgrip strength assessed at hospital discharge. Fifty-seven percent of the cohort was re-admitted to the hospital at least one time and 11.4% died during the 12-month follow-up. Because of the small number of deaths, the analysis was performed using a unique composite outcome. After adjustment for potential confounders patients with higher grip strength tended to have a lower risk of rehospitalization or death over the 12-month follow-up (OR of 0.68 for patients in the highest tertile compared to those in the lowest tertiles) but the difference was not statistically significant in this small sample.

Table 3 Adjusted odds ratios for rehospitalization or death during the follow-up according to handgrip strength tertiles at discharge in men and women

Model 1: adjusted for age, gender; Model 2: adjusted for age, gender, and BMI; Model 3: adjusted for age, gender, BMI, MMSE, BADL 15 days before hospital admission, and CIRS Total Score.


In this sample of older acute medical inpatients, handgrip strength correlated with age, gender, nutritional status, and objective measures of lower extremity performance (SPPB score). Greater handgrip strength, assessed at hospital admission, was also significantly correlated with the length of hospital stay, independent of potential confounders, including age, BMI, comorbidity, cognitive status, self-reported functional status, and SPPB score. Conversely, grip strength assessed at time of hospital discharge was not related to the risk of rehospitalization or death in the year following hospital discharge, although a non significant trend was observed among men. To the best of our knowledge, this is the first attempt to assess the prognostic value of handgrip strength in hospitalized older patients.

Our findings extend to the acute clinical setting, the results of previous epidemiological studies on the relationship of handgrip strength with age, gender, and anthropometric measures. Previous investigations consistently demonstrated the predictive value of grip strength in term of functional decline, disability, risk of hospitalization, and mortality in older persons. In line with these studies we demonstrated the potential prognostic value of grip strength in term of length of hospital stay, a proxy measure of health status and length of recovery (27). In contrast with other studies we were not able to demonstrate a significant association between grip strength and the risk of hospitalization or death over the follow-up. The small sample size with reduced statistical power might explain, at least partially, this unexpected result. Most of the studies investigating the prognostic value of handgrip strength in older persons were conducted in community dwelling people (28). Our study demonstrates the feasibility of grip assessment in hospitalized acutely ill older patients, and suggests a potential prognostic value.

Handgrip strength remained substantially stable during hospital stay, and this could be the result of  the complex interactions between several determinants. In fact, handgrip strength is influenced both by muscular and non-muscular factors including cardiovascular function, cognitive, and affective status, mid- and late life habits, and physical activity. Grip strength is proven to track over the lifespan: the greater is handgrip strength in midlife, the better will be physical status in late life and the lower will be the risk of becoming disable, regardless of comorbidities (9). Handgrip strength has been found to correlate with strength of other muscle groups and to be a good indicator of health status and body resilience. Furthermore, some studies showed that muscle strength may decline more quickly than muscle mass (29) and that low handgrip strength might be considered a better indicator of functional reserve compared to loss of muscle mass (11). In this perspective handgrip strength, combined with bioimpedance analysis and gait speed assessment, has been recently suggested for the clinical definition of sarcopenia (30).

It is still unclear which is the precise biological mechanism linking poor handgrip strength and declining trajectory of patient’s health status. It is likely that poor grip strength could be either the expression of subclinical diseases or the consequence of reduced physical activity, which itself exposes an individual to a greater risk of adverse events. Furthermore, like other objective measures of functional status, grip strength assessment may capture the integrated and multisystemic effects of aging, comorbidity, disease severity, malnutrition, motivation, and cognition (31, 32) on the health status of older persons.

Finally, two important limitations of this study should be noted. First, this study was conducted on a small size sample and this reduced its statistical power. Second, because of the restricted inclusion criteria these results might have a limited external validity. In order to gain more information about the clinical significance of handgrip strength it’s desirable to examine a larger size sample.

In conclusion, assessment of handgrip strength, a simple and inexpensive objective functional measure, might provide important prognostic information in hospitalized older patients and it can be considered a reliable alternative for the functional evaluation of patients unable to walk. Further longitudinal studies with greater sample size and adequate statistical power are needed to confirm these preliminary results.

Acknowledgments: This research was supported in part by contracts from the National Institute on Aging, Intramural Research Program, NIH.



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