BIA muscle quality evaluation -
Here's a painless and easy way to estimate body fat. In addition to the bathroom scale, how our clothes fit, and how we feel day to day, body fat measurements provide us with a bit more information about where we stand with our health and fitness goals.
Simply put, getting your body composition estimated provides information about how much of your body is fat and not fat muscle, bone and organs. You are likely aware that too much body fat is a reason for concern.
Carrying too much fat especially around the middle increases the chance of developing conditions such as type 2 diabetes, heart disease, hypertension, and joint disease. One method of estimating body fat is through bioelectrical impedance BIA.
It is a painless and easily accessible procedure that is safe for most individuals. Those with a pacemaker or women who are pregnant should avoid the test. The test works by passing a low level imperceivable current through the body.
The current moves faster through fat-free mass, due to its higher water content, than fat mass. The resistance that the current encounters is measured and then plugged into a mathematical equation to come up with total body water, fat-free mass, and body fat.
In the present study, the frequency of sarcopenia based on the assessment using BIA was relatively low compared with that using CT.
Therefore, the diagnosis of sarcopenia in the decompensated phase should be appropriately evaluated by a cross-sectional area of several muscles on CT imaging. As a diagnostic method, CT imaging plays a critical role in the early detection of sarcopenia [ 20 ]. This criterion could be applicable to various fields to diagnose disease-related sarcopenia.
However, muscle mass in patients with edema and ascites may be overestimated, and the frequency of sarcopenia may not be accurately assessed. If patients with CLD are overestimated by using the BIA method to assess sarcopenia, appropriate treatment, such as nutritional and exercise interventions, may be delayed and may affect prognosis [ 21 ].
It is well known that CLD with disease-related sarcopenia is associated with a poor prognosis. Therefore, accurate diagnoses are important to improve the overall prognoses in patients with disease-related sarcopenia [ 22 ].
Iwasa et al. SMI, which uses upper and lower limb muscle mass, has been shown to be unsuitable for patients with lower limb edema. In addition, when using BIA, patients with ascites or edema may want to consider the cut-off value and evaluate sarcopenia only by using the upper arm, which is less susceptible to edema.
Furthermore, the measurement of the skeletal muscle mass by BIA varies depending on the device. Different devices were used, which might add extra variability and lead to misdiagnosis. In fact, there is a great difference between InBody S10 and MC as follows.
The difference of frequencies from these two BIA devices influences the assessment of body composition in cirrhotic patients [ 24 ].
It is unclear to what degree violating BIA measurement assumptions will alter the predicted SMI. In the present study, the frequency of sarcopenia based on two different devices was similar despite acutely violating the preliminary measurement BIA assumptions across a range of different methods.
The minor variations of the measurement may be smaller than what would be expected [ 26 ]. This study has some limitations.
First, it was a retrospective study. Second, edema was not assessed. Fluid retention can only be examined in ascites. Third, the equipment used for the BIA differs between the two facilities in this study. When evaluating SMI in pathological conditions accompanied by fluid retention such as liver cirrhosis, it is important to select an appropriate BIA measuring device and also evaluate water content by site.
We will investigate this and report it in an upcoming article. Due to the characteristics of the measurement principle of BIA, overestimation of muscle mass is predicted to be affected by fluid retention. It is necessary to assess edema before determining muscle mass using the BIA method.
We thank the Statista Corporation for assistance with the statistical analyses. We also thank Robert E. Brandt, Founder, CEO, and CME, of MedEd Japan, for editing and formatting the manuscript.
This study protocol was reviewed and approved by the Institutional Review Board Ethics Committees of Tokushukai Medical Group Number: TGE and Kitasato University School of Medicine Number: C This study was a retrospective observational study.
Informed consent was obtained from all individual participants included in the study by the opt-out method of our hospital Website, which was approved by the Research Ethics Committees of Tokushukai Medical Group and Kitasato University School of Medicine.
Nahoko Kikuchi, Haruki Uojima, Hisashi Hidaka, Shuichiro Iwasaki, Naohisa Wada, Kousuke Kubota, Takahide Nakazawa, Akitaka Shibuya, Makoto Kako, Teruko Sato, and Chika Kusano contributed equally to this work; Nahoko Kikuchi and Haruki Uojima collected and analyzed the data; Haruki Uojima drafted the manuscript; Hisashi Hidaka and Makoto Kako designed and supervised the study; Shuichiro Iwasaki, Naohisa Wada, Kousuke Kubota, Takahide Nakazawa, Akitaka Shibuya, Teruko Sato, and Chika Kusano offered technical or material support.
The technical appendix, statistical code, and dataset are available from the corresponding author email: kiruha kitasato-u. All data generated or analyzed during this study are included in this article.
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filter your search All Content All Journals Annals of Nutrition and Metabolism. Advanced Search. Skip Nav Destination Close navigation menu Article navigation. Volume 78, Issue 6.
Materials and Methods. Statement of Ethics. Conflict of Interest Statement. Funding Sources. Author Contributions. Data Availability Statement. Article Navigation. Research Articles August 18 Evaluation of Skeletal Muscle Mass in Patients with Chronic Liver Disease Shows Different Results Based on Bioelectric Impedance Analysis and Computed Tomography Subject Area: Endocrinology , Further Areas , Nutrition and Dietetics , Public Health.
Nahoko Kikuchi ; Nahoko Kikuchi. a Department of Nutrition, Kitasato University Hospital, Sagamihara, Japan. k kitasato-u. This Site. Google Scholar. Haruki Uojima ; Haruki Uojima. b Department of Gastroenterology, Internal Medicine, Kitasato University School of Medicine, Sagamihara, Japan.
c Department of Gastroenterology, Shonan Kamakura General Hospital, Kamakura, Japan. Hisashi Hidaka Hisashi Hidaka. Shuichiro Iwasaki ; Shuichiro Iwasaki. Naohisa Wada Naohisa Wada. Kousuke Kubota ; Kousuke Kubota.
Takahide Nakazawa ; Takahide Nakazawa. Akitaka Shibuya ; Akitaka Shibuya. Makoto Kako ; Makoto Kako. Akira Take ; Akira Take. d Department of Microbiology, Kitasato University School of Medicine, Sagamihara, Japan.
Yoshihiko Sakaguchi ; Yoshihiko Sakaguchi. Teruko Sato Teruko Sato. Chika Kusano Chika Kusano. Ann Nutr Metab 78 6 : — Article history Received:. Cite Icon Cite.
However, it is the implementation of assessment methods due to cognitive impairment and reduced physical functioning that shows difficulties. Mainly the SARC-F could not be answered by some residents and the validity remains questionable. The use of the PhA does not provide any additional benefit for sarcopenia quantification compared to previously used assay methods, such as MHF and ASMM.
Due to the small sample size, PhA cannot be recommended as an additional parameter for sarcopenia quantification in our study. The use of PhA to quantify sarcopenia among NH residents remains questionable.
The preliminary stage of sarcopenia cannot associate with the PhA. Further limitations are due to the lack of knowledge by PhA cut-off values for different BIA devices and the benefit for progression monitoring, which represent further goals in sarcopenia quantification according to EWGSOP2 specifications.
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We would like to thank all nursing homes, assessors and residents who participated in the study. Also, thanks to the BaSAlt project team members. Open Access funding enabled and organized by Projekt DEAL. This research was funded by the German Federal Ministry of Health —, grant number ZMVIFSB Department of Sports Medicine, University Hospital of Tuebingen, , Tübingen, Germany.
Interfaculty Research Institute for Sport and Physical Activity, University of Tuebingen, , Tübingen, Germany. Institute of Sport Science, Faculty of Economics and Social Sciences, Eberhard Karls University of Tuebingen, , Tübingen, Germany.
You can also search for this author in PubMed Google Scholar. All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by DH and SW.
The first draft of the manuscript was written by DH, SW, AT, and AMN. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Correspondence to Daniel Haigis. The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of the Faculty of Economics and Social Sciences at Eberhard Karls University Tübingen No.
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et al. Bioelectrical impedance analysis in the BaSAlt cohort-study: the phase angle as an additional parameter for sarcopenia quantification among German nursing home residents?. Eur Geriatr Med 14 , — Download citation.
Use Evluation BIA Scale to Meet Fitness and Weight Loss Goals. Anisha Diuretic effect on fluid balance, MD, is a board-certified evalation, Digestive aid with probiotics and prebiotics cardiologist, and fellow of muuscle American College egaluation Cardiology. Adah is an occupational therapist, working in the area of pediatrics with elementary students with special needs in the schools. Her work as an occupational therapist includes: home health, acute care, chronic care, seating and positioning, outpatient rehab, and skilled nursing rehab. Bioelectrical impedance analysis BIA measures body composition based on the rate at which an electrical current travels through the body.BIA muscle quality evaluation -
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Citation: Cáñez-Ríos M, Esparza-Romero J, González-Arellanes R, Ramírez-Torres M, Figueroa-Pesqueira G, Urquidez-Romero R, Rangel-Peniche DB and Alemán-Mateo H External validation of BIA equations to estimate appendicular skeletal muscle mass in older adults: Importance of the bias analysis and derivation of correction factors to achieve agreement.
Received: 23 May ; Accepted: 25 July ; Published: 25 August Copyright © Cáñez-Ríos, Esparza-Romero, González-Arellanes, Ramírez-Torres, Figueroa-Pesqueira, Urquidez-Romero, Rangel-Peniche and Alemán-Mateo.
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No use, distribution or reproduction is permitted which does not comply with these terms. Body Composition Assessment Techniques in Clinical and Epidemiological Settings: Development, Validation and Use in Dietary Programs, Physical Training and Sports.
Export citation EndNote Reference Manager Simple TEXT file BibTex. Check for updates. ORIGINAL RESEARCH article. Introduction Skeletal muscle performs a broad range of mechanical, structural and metabolic functions 1.
Materials and methods This is a secondary analysis generated from various studies with a cross-sectional design 33 — 35 and the baseline data of one randomized clinical trial 36 carried out in the Body Composition Laboratory of the Food and Development Research Center, CIAD, A.
While it is well documented that men generally have greater muscle mass than women 34 , 35 , few studies of sex differences in neural factors are available. However, some studies have revealed that the firing rate of the vastus medialis differed between women and men 36 , and less steady force production in women was caused by unstable modulation of the motor firing discharge rate Moreover, BIA cannot evaluate such neural factors and only reflects morphological factors, which may explain the differences in the correlation and accuracy of the estimation model between the sexes in this study.
Another possible explanation was that BIA could not evaluate the difference in the fiber characteristics of the lower limb muscles between men and women. A previous study revealed that type II fibers, which could produce more force than type I fibers, which are more suitable for continuous force production, are larger in men than in women Further, BIA could not distinguish muscle fiber types, which might have influenced the correlation and accuracy of the estimation model between the sexes in this study.
Our findings might help athletic trainers or fitness professionals resolve the concerns about the time-consuming and unsafe nature of 1RM measurements.
Additionally, these results might potentially be applied in rehabilitation settings, where safety concerns are more important for future studies. This study had some limitations.
First, although sample size calculation was conducted prior to the study initiation, the sample size was too small to draw a clear conclusion regarding the validity and reproductivity of the established prediction models. Hence, a study with a larger sample size should be conducted to confirm our results and their validity and reproductivity in the future.
Second, our target population was healthy young adults, not older adults or people with pain or past injuries.
Since SMM might not play an important role in muscle strength among healthy older adults 39 and muscle strength was lower in people with a history of injuries or low back pain compared to those without those problems 40 , 41 , the correlations and estimation models in our study could not be directly adapted to these populations.
To address this issue, multivariable estimation models, adaptive to any population, should be developed in future studies. Finally, since the absolute SMM value reportedly differed among body composition analyzers 42 , the relationship and accuracy of the estimation models may differ from those of other BIA equipment.
Therefore, the correlation and accuracy of the estimation model using other equipment should be confirmed in future studies.
In conclusion, 1RM for LP and BIA measurements were strongly correlated, and accurate 1RM prediction from BIA measurements might be attainable in healthy young adults.
This methodology might provide a new perspective for sports or fitness experts to resolve the safety and time-consuming concerns for 1RM measurements. The application of our results to rehabilitation medicine might also be expected in future studies.
This cross-sectional study protocol was approved by the institutional ethics committee of Shinshu University approval number: This study was conducted in accordance with the Declaration of Helsinki and was revised in Healthy adults working as medical staff at Kakeyu-Misayama Rehabilitation Center, Kakeyu Hospital, Japan, were conveniently recruited via a displayed poster between July and November First, the body composition was measured using BIA, and then the 1RM was measured.
Both assessments were conducted at a fixed time on the same day. Participants were instructed to refrain from eating or drinking large amounts of water 4 h before the measurements and consuming alcohol 8 h before the measurement.
Participants were also required not to undertake any intense exercise for 8 h before the measurements. BIA measurements were performed using a portable body composition analyzer Inbody Biospace, Korea , equipped with a terra-polar eight-point tactile electrode system.
The measurements by multi-frequencies are considered a better method for assessing muscle function than the single-frequency measurement A portable body composition analyzer from the Inbody models was confirmed as a reliable and valid tool to assess the SMM in healthy men and women and is considered to have sufficient ability to assess the body composition such as SMM, body fat, and body fat percent like other advanced models Moreover, the Inbody has been widely used to assess SMM, especially for the Japanese population, in various studies, including large sample cohort studies 44 , 45 , 46 , 47 , The measurements took approximately 40 s to complete.
The analyzer calculated the absolute muscle and fat mass, body fat percentage, and segmental muscle mass values upper and lower limbs of both sides and trunk. This resistance training machine allowed the participants to lift the loads unilaterally.
The 1RM procedure was performed according to the American College of Sports Medicine guidelines All participants underwent a 5-min warm-up session using an ergo cycle bike before the measurements.
The participants sat on the LP machine with their hip and knee joints fixed at approximately 90°, and the pelvis was stabilized by the belt. The participants were also required to hold handgrips placed on both side of the machine seat with each hand.
The load in the measurement was progressively changed by 3—10 kg until the participants could not lift the loads. The goal was to complete a maximal lift in five attempts, and 3—5 min of rest were provided between sets.
All tests were performed by the same evaluator in the same order. Since moderate-to-strong correlations between BIA measurements and isometric muscle strength of the lower limbs have been previously reported 21 , 25 , 26 , 27 , we set the alpha to 0.
First, we confirmed the normality of the obtained data using the Shapiro—Wilk test, and we also confirmed the homogeneity between the sexes by unpaired t-test. Finally, to create the 1RM prediction models, a simple linear regression analysis was performed with BIA measurements as independent variables.
All analyses were performed using SPSS version 25 International Business Machine Corp. The datasets used in this study are available from the corresponding author upon reasonable request. El-Kotob, R. et al. Resistance training and health in adults: an overview of systematic reviews. Article PubMed Google Scholar.
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Magnusson, S. The muscle strength testing followed by hand force measurement. The maximum hand force MHF of the residents was tested using an isometric hand force dynamometer Hydraulic Hand Force Dynamometer Saehan Model SH, Saehan, Changwon-si, Korea.
Three measurements each were taken alternating the right and left hand. The best trial out of six was used for the maximum force value. The measurement was performed in sitting position and flexion 90° in upper to lower arm.
Confirmation of sarcopenia was checked by muscle mass determination. BIA measurement was taken in horizontal lying position without upper body inclination 0° and abduction of arms 30° and legs 45° , respectively. The measurement should be conducted in the morning before breakfast.
For further analysis, generated data was transferred into BodygramPlus Enterprise software Version 1. To determine the severity of sarcopenia, the physical functioning of the residents was assessed using the 4 m-walking-speed-Test.
Habitual gait speed 4MWS was recorded over a walking distance of four meters and measured using a stopwatch. Before and after the measured distance, run-on and run-off distances of two meters each are considered.
Residents who were not able to walk e. wheelchair users were classified as functional impaired. Figure 1 shows the sarcopenia quantification based on the adapted EWGSOP2 specifications in the BaSAlt cohort-study.
Sarcopenia quantification in the BaSAlt cohort-study modified after [ 3 ]. Further body composition parameters were recorded as a part of BIA measurement. The reactance Xc and resistance Rz were measured. Additionally, phase angle PhA , fat mass FM , fat-free mass FFM , muscle mass MM , total body water TBW , extracellular water ECW , and body cell mass BCM were calculated.
For the parameters FM, FFM, and MM, the values adjusted for body size were also calculated. Data analysis was performed with the statistical program SPSS IBM SPSS version For descriptive analysis median values Md with range minimum—maximum , mean with standard deviation, and percentages were collected.
For the group comparisons, non-parametric analysis with Kruskal—Wallis-Tests were used. Post-hoc-Tests for comparison between the sarcopenia groups, adapted by Bonferroni-correction, were measured. For three residents, an analysis of data could not be done, because one resident died, one resident left the NH, and another resident transitioned to palliative care during the measurement time t1.
For the sarcopenia quantification, the data from 78 residents from fife NH was analyzed. Missing values are described for the respective assessments and were not considered in the analysis.
The evaluation of the morbidity status could be determined for 77 residents, because for one resident the access to the medical file was denied. The evaluation of the MMST could not be determined for 12 residents. Also, MHF was not possible to assess for two residents, because they had severe cognitive impairment.
The 4MWS were missed for 14 residents. The study characteristic and sarcopenia quantification with Kruskal—Wallis-Tests, Dunn-Bonferroni post-hoc-Tests, and Pearson correlations between PhA and the other variables assessed in the BaSAlt cohort are shown in Table 1 and Table 2.
In addition, BIA parameter for body composition and supplementary group descriptions are presented in Tables 3 and 4. BI Barthel-index, MMST mini-mental-status-test, MNA-SF ® mini-nutrition-assessment-short-form. The BaSAlt cohort-study shows multimorbid NH residents in its results. Cognitive and physical impairments play key roles in sarcopenia quantification, as they severely limit the implementation of recommended assessment methods according to EWGSOP2 specification.
Difficulties in implementation are mainly noticeable for the SARC-F and 4MWS. On the other hand, most residents were able to complete the required assessments for MHF and ASMM. This provides an opportunity for BIA to further sarcopenia diagnose using the muscle quality parameter PhA.
But the specific focus on PhA and sarcopenia quantification has a lack of research that needs to be addressed by further studies. Our study did not reveal any problems with the implementation of the BIA in the respective NH.
The reason for this could be that it is used while the residents are measured in spine position. This leads to a higher acceptance among the residents and immobile residents can also be measured.
Previous BIA measurements were implemented using BIA by standing position. However, it should be mentioned here that the comparison of different measurement methods and BIA devices is not recommended [ 27 ].
A standardization in the NH must take place in order to ensure a reliable data base. The limitation of comparability also refers to the cut-off values, which are given for the ASMM but not described for the PhA in the EWGSOP2 specifications.
This must be enabled in prospective studies. However, the differences within the age groups are not recorded more precisely, so that a rough orientation for the reference values is given. A systematic review by Di Vincenzo and colleagues examined PhA values specifically in relationship with sarcopenia.
Significantly lower PhA values could be determined for sarcopenic individuals. Furthermore, higher prevalence of sarcopenia was recorded among people with lower PhA, such as cancer and geriatric patients [ 28 ]. Reference values for PhA were determined for the German population, but with a different BIA device and without setting-specific consideration than in our study [ 29 ].
From our point of view, these described references cannot be used for an evaluation of our BaSAlt cohort-study, as different sarcopenia quantification methods were collected in different settings and BIA devices. To the best of our knowledge, our study is the only one in Germany that has addressed the differences of PhA in relation to sarcopenia quantification among multimorbid NH residents according to EWGSOP2 specifications.
We hypothesized that PhA has the property for quantifying sarcopenia among NH residents. We can confirm this point, but we limit this statement due to the results of the comparisons of the three sarcopenia groups in our study.
It can be concluded that the prediction of PhA is limited in the preliminary stage of sarcopenia. Considering the prevention and treatment of sarcopenia, this seems to be an unfavorable outcome.
Thus, especially in the transition from non-sarcopenic to pre-sarcopenic NH residents, no significance can be determined by the use of PhA. The study by Kołodziej et al. Accordingly, PhA is an additional parameter in the prognosis of pre-sarcopenia.
Regular measurement using BIA is suggested among geriatric patients to minimize the risk of sarcopenia [ 30 ]. On the other hand, when considering sarcopenia, the individual is often forgotten due to various population-specific reference values and algorithms [ 31 ].
Measuring PhA over time span can also be used to document individual progress monitoring. Mainly for vulnerable individuals, such as NH residents, this could be a helpful tool to monitor the course and progression of the musculoskeletal disease sarcopenia.
For the standardized analysis of the PhA, trained staff, identical BIA devices, as well as time slots are needed. This should enable future reference values to provide scientific results. The BaSAlt team trained assessors in the use of the BIA device in standardized two training-days.
In addition, the target for measuring body composition was set for the morning before breakfast in order to minimize shifts in fluid quantity and food intake. However, it was not always possible to satisfy that target, as the prevailing COVID pandemic made it a priority to ensure primary care for NH residents.
Furthermore, due to the pandemic situation and regulations for the uniform protection of residents in German long-term care settings, physical activity may have been negatively influenced.
Physical activity shows positive correlations with increasing PhA [ 32 ]. Therefore, the contact restrictions and isolations of residents during the times of the COVID pandemic may have influenced physical activity and thus PhA in our study. Although, a limited number of residents were included in our study.
This is reflected in the respective group sizes. We suspected a higher number of "confirmed sarcopenia" residents according to previous quantification studies.
However, it is the implementation of assessment methods due to cognitive impairment and reduced physical functioning that shows difficulties. Mainly the SARC-F could not be answered by some residents and the validity remains questionable. The use of the PhA does not provide any additional benefit for sarcopenia quantification compared to previously used assay methods, such as MHF and ASMM.
Due to the small sample size, PhA cannot be recommended as an additional parameter for sarcopenia quantification in our study. The use of PhA to quantify sarcopenia among NH residents remains questionable. The preliminary stage of sarcopenia cannot associate with the PhA.
Further limitations are due to the lack of knowledge by PhA cut-off values for different BIA devices and the benefit for progression monitoring, which represent further goals in sarcopenia quantification according to EWGSOP2 specifications. Cruz-Jentoft AJ, Montero-Errasquín B, Morley JE Definitions of Sarcopenia.
In: Cruz-Jentoft AJ, Morley JE eds Sarcopenia, 1st edn. Wiley-Blackwell, New Jersey, pp 19— Chapter Google Scholar. Füzeki E, Banzer W Bewegung und gesundheit im alter.
In: Banzer W ed Körperliche aktivität und gesundheit, 1st edn. Springer Verlag, Berlin, pp — Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyère O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA et al Sarcopenia: revised European consensus on definition and diagnosis.
Age Ageing.
Can phase BIA muscle quality evaluation nuscle an BIA muscle quality evaluation parameter evaluatiom BIA muscle quality evaluation sarcopenia among German nursing home residents? Nourishing recovery recipes impedance analysis and determination of wuality angle represent chances in the diagnostic of sarcopenia, but there musdle a limitation for differentiation in preliminary stage of sarcopenia among multimorbid NH evaaluation. Sarcopenia is characterized evaluaton the loss of muscle mass, strength, and physical functioning. The bioelectrical impedance analysis BIA is a simplify method for the measurement of muscle quantity and quality. But there is a lack of evidence in the interpretation of the muscle quality parameter phase angle PhAwhich was recommended by the European Working Group on Sarcopenia in Older People 2 EWGSOP2. We hypothesize that the PhA shows differences between sarcopenia categorized groups and can be used as an additional parameter for sarcopenia quantification among residents of nursing homes NH. Based on EWGSOP2 specifications, 78 residents from five German NH was categorized into sarcopenia groups. The rising evaaluation index of Controlled eating frequency populations necessitates the continuous evolution of geriatric assessment methods, especially wvaluation ones used to Digestive aid with probiotics and prebiotics frailty and BIA muscle quality evaluation qualitg of frailty. Juscle appropriately early diagnosis of adverse changes in skeletal muscles can reduce the risk of functional limitations in elderly persons. The aim of this study was to assess the correlation between the appendicular skeletal muscle mass and quality, estimated by the bioelectrical impedance analysis method, and the risk of prevalence of the pre-frailty state in elderly persons. One-thousand-and-fifteen subjectively healthy persons aged 60—87 years were tested. Anthropometric measurements and physical fitness and activity measurements were carried out and the frailty phenotype was evaluated.
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