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BIA lean body mass evaluation

BIA lean body mass evaluation

Salamone LM, Fuerst T, Evaluarion M, Kern Lesn, Body cleanse for energy T, Dockrell M, et al. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Biolelectric Impedance Analysis BIVA The BIVA, as outlined by Professor A. List of Partners vendors. Article PubMed PubMed Central Google Scholar. Buckinx, F. Download ePub.

BIA lean body mass evaluation -

Moreover, the accurate and timely diagnosis of sarcopenia in patients with T2DM is crucial since it may lead to specific therapeutic interventions, including nutritional therapy, strength exercise training, adequate assessment of other complications and adjustment of medication to prevent hypoglycemia [ 7 ].

Diagnosis of sarcopenia necessitates both low muscle strength and documentation of low muscle quantity or quality. While magnetic resonance imaging MRI and computed tomography CT are considered the most accurate tools to assess muscle quantity, these methods are costly and often unavailable.

Dual-energy X-ray absorptiometry DXA is a reference method for the assessment of body composition in the research field due to its fast acquisition time, low radiation exposure and relatively low cost.

The method measures the attenuation of low-emission X-rays as they pass through body tissues high attenuation through bone and low attenuation through fat [ 15 ] in the whole body and in standard regional body composition measurements trunk, arms, legs, android and gynoid regions [ 16 ].

DXA estimates for body composition have been extensively compared to other body composition assessment techniques such as hydrostatic weighing, CT and MRI [ 17 , 18 , 19 , 20 ], and are increasingly used as a reference tool for newer body composition techniques.

The main weaknesses of DXA are its limited availability, its inability to measure very tall or obese individuals and the effect of body thickness on muscle mass measurements [ 21 ].

Measurement of body composition by electrical conduction instruments Body Impedance Analyze; BIA is a widely used method for assessing body composition.

The method measures the electrical properties of body tissue and evaluates body composition parameters that include total-body water TBW , lean body mass LBM or fat free mass, FFM and fat mass FM. BIA is a non-invasive, affordable, portable, and reliable method of body composition evaluation.

The basic principle of the BIA is that the transit time of a low-voltage electric current through the body depends on the characteristics of the body composition [ 22 ].

However, this methodology has potential limitations resulting from the chemical composition of FFM i. Older adults with T2DM may have significant alterations in body fluids due to coexisting diabetes related complications such as heart failure [ 24 ] , therapeutic agents [such as thiazolidinediones [ 25 ], insulin [ 26 ] and sodium-glucose cotransporter-2 SGLT-2 inhibitors [ 27 ] among others] and direct effects of hyperglycemia [ 28 ], which may potentially affect the validity of body composition assessment using BIA.

Previous studies assessed the validity of a commonly used direct segmental multi-frequency bioelectrical impendence analysis DSMF-BIA tool InBody analyzer in the general middle-aged adult population [ 29 ] as well as in obese middle-aged women [ 30 ].

However, to the best of our knowledge, no studies reported the validity of DSMF-BIA in older adults with T2DM. A recent review paper published by Sbrignadello et al. Therefore, the aim of this study was to test the agreement between the DSMF-BIA and DXA in older adults with T2DM at baseline and during treatment with commonly used therapeutic interventions, which may affect body composition and body fluids including diet, exercise and empagliflozin.

The CEV study [ 32 ] took place at the institute of Endocrinology, Metabolism, and Hypertension IEMH , Tel-Aviv Sourasky Medical Center between May and February The study was approved by the Tel-Aviv Sourasky Medical Center Institutional Review Board. The present study is a post hoc analysis conducted in a population sampled from this study.

Over older adults with T2DM were screened according to the eligibility criteria described in [ 32 ]. Details of the full study design of the CEV study are available in [ 32 ] PRS: NCT Briefly, after screening and collection of baseline measurements, subjects were randomly allocated to a week intervention period in one of three groups: 1.

The final study population included older adults with T2DM 60 women. Eighty-four participants 49 women had a body composition assessment both by DXA; Lunar Prodigy, GE Healthcare, Madison, WI, USA and DSMF-BIA InBody body composition analyzer, Cerritos, CA, USA at baseline.

After 10 weeks of intervention 7 4 women , 10 5 women and 11 8 women participants had both measurements of DXA and DSMF-BIA in the CRT, diet or empagliflozin intervention groups, respectively.

DSMF-BIA: Measurements were obtained using a InBody body composition analyzer Cerritos, CA, USA in the standing position.

DXA: DXA scan was performed using a Lunar Prodigy DXA scanner GE Healthcare, Madison, WI, USA. Scan modes thick, standard, or thin were automatically set by the software. In addition to total-body composition, regional estimates were made for the arms, legs, and trunk.

This was accomplished by manually adjusting cut positions for each region of interest ROI. A detailed list of the outcomes assessed in the CEV trial can be found in ref. Height and waist circumference measured around the umbilicus were measured twice, and the average was then calculated, according to a standardized protocol.

Glycemic control was determined by fasting plasma glucose and HbA1c. Statistical analyses were performed using SPSS version We used two methods to evaluate the degree of agreement between the DXA indices and DSMF-BIA: 1 Bland—Altman plots; 2 the Intraclass Correlation Coefficient ICC.

We used a Bland—Altman plot with regression analysis, to show the differences between the indices, vs. their mean. Sex stratified means were analyzed and the effect modification of sex for the agreement between the DSMF-BIA and the DXA was tested.

Baseline subject characteristics are detailed in Table 1. Overall mean age was DSMF-BIA distribution is represented by the left box in each sub-figure; DXA distribution is represented by the right box in each sub-figure. ASMI appendicular skeletal mass index, DSMF-BIA direct segmental multi-frequency bioelectrical impendence analysis, DXA dual-energy X-ray absorptiometry.

The results of DSMF-BIA and DXA are shown in Table 2. Mean levels of lean mass segments significantly differed between the methods with a maximal difference of — 1. Fat differences between the methods were significantly different with a maximal arm fat mass difference overestimated by 2.

Sex was not found to be an effect modifier sex stratified mean levels of both lean and fat segments can be found in the supplementary file; Table S1. Examination of the agreement between the methods according to specific parameters of body composition are presented in Table 2 , Fig.

The degree of agreement was further tested using the Bland—Altman method Table 2 , Table S1 , Fig. Comparing the agreement between the methods on arms LBM showed a mean difference of 0.

For lean mass in the legs and trunk, as well as for ASMI, there was an agreement between the methods Fig. There was no agreement between the DSMF-BIA and the DXA methods for all fat measures except total fat percentage Table 2 and Fig.

Total fat percentage bias was 1. Agreement for total fat percentage remained for sex when analyzed separately Table S1 and Fig. Following 10 weeks of empagliflozin, CRT or a V-Med diet the trends for lean mass remained with arm LBM overestimated, legs LBM and ASMI underestimated, and fat percentage overestimated by the DSMF-BIA in all interventions Table 3 and Fig.

Despite having profound effects on body composition, the different interventions did not seem to affect the high agreement between DXA and DSMF-BIA.

Bland—Altman plots presenting the difference between DSMF-BIA and DXA vs. The solid line represents the mean bias and the broken line the ±1. Mean bias is considered the mean difference of all individuals between DSMF-BIA and DXA.

ASMI appendicular skeletal mass index, DSMF-BIA direct segmental multi-frequency bioelectrical impendence analysis, DXA dual-energy X-ray absorptiometry, LBM lean body mass. Our results clearly show that assessing body composition and diagnosing sarcopenia using the DSMF-BIA method is comparable to the DXA scan in older adults with T2DM.

This was not affected by a week intervention period with treatment modalities often used in the treatment of T2DM. The degree of agreement between the methods was overall better when comparing parameters of LBM than parameters of FM.

For diagnosing sarcopenia in the clinical setting, DSMF-BIA had high specificity and high negative predictive value, suggesting it may be a useful screening tool for this condition.

Discrepancies between DXA and DSMF-BIA have been previously noted in different populations. This discrepancy highlights the importance of validation of DSMF-BIA in different populations and under different physiologic interventions.

Given the increasing rates of diabetes in general and in older adults in particular [ 2 ] and the wide use of BIA methods in studies testing diabetes and sarcopenia outcomes [ 31 ], it is not surprising that there was a call for validation studies testing the accuracy of BIA for this population [ 31 ].

Using DXA as a method to diagnose sarcopenia has several inherent limitations. DXA scan is less accessible and more expensive than DSMF-BIA.

Very tall and very obese individuals cannot be adequately measured in a standard DXA machine and body thickness and hydration status e. Moreover, to ensure the accuracy of any method for assessing muscle mass, standardization is needed. Calibration of materials and equations used to derive lean mass should be standardized across manufacturers.

It is important to standardize the local regions of interest, such as trunk, arms, legs, which are different across manufacturers. Finally, defining a reference population in the same way as has been achieved for the use of DXA in diagnosing osteoporosis should be considered [ 43 ].

The strengths of this manuscript include its relatively large population, its prospective nature and focus on a relatively poorly studied population of older adults with diabetes and low physical activity level. Moreover, we present the lack of a significant effect of commonly used interventions for the treatment of T2DM on the validity of DSMF-BIA.

Its weaknesses include the limited sample size in the prospective phase, the relatively short period of follow up and the fact that the study was not specifically designed to validate MF-BIA vs.

Also, the validity tested in the current paper is limited to relatively young older adults with T2DM who have limited rate of complications with low levels of sarcopenia. In that sense the significance of the findings presented here are important for early detecting lower muscle mass for early prevention, but with the cost of limited external validity.

In conclusion, the DSMF-BIA as compared to DXA is a reliable screening technique for sarcopenia in older patients with T2DM.

Accurate and accessible diagnosis of sarcopenia is crucial in older subjects with diabetes and directly affects clinical decisions and treatment [ 44 , 45 , 46 ]. The routine use of DSMF-BIA as a screening tool for sarcopenia in clinics treating older patients with diabetes should be considered.

World Health Organization. World report on ageing and health. Mathus-Vliegen EMH. Obesity and the elderly. J Clin Gastroenterol. Article PubMed Google Scholar. Volpi E, Nazemi R, Fujita S. Muscle tissue changes with aging.

Curr Opin Clin Nutr Metab Care. Wang DXM, Yao J, Zirek Y, Reijnierse EM, Maier AB. J Cachexia Sarcopenia Muscle. Article CAS PubMed Google Scholar. Yeung SSY, Reijnierse EM, Pham VK, Trappenburg MC, Lim WK, Meskers CGM, et al. Article PubMed PubMed Central Google Scholar. Xu J, Wan CS, Ktoris K, Reijnierse EM, Maier AB.

Sarcopenia Is Associated with Mortality in Adults: A SystematicReview and Meta-Analysis. Sinclair AJ, Abdelhafiz AH, Rodríguez-Mañas L. Frailty and sarcopenia—newly emerging and high impact complications of diabetes.

J Diab Complicat. Article Google Scholar. Liccini AP, Malmstrom TK. Frailty and sarcopenia as predictors of adverse health outcomes in persons with diabetes mellitus. J Am Med Dir Assoc.

Pacifico J, Geerlings MAJ, Reijnierse EM, Phassouliotis C, Lim WK, Maier AB. Prevalence of sarcopenia as a comorbid disease: A systematic review and meta-analysis. Exp Gerontol.

Umegaki H. Sarcopenia and frailty in older patients with diabetes mellitus. Geriatr Gerontol Int. Ida S, Kaneko R, Nagata H, Noguchi Y, Araki Y, Nakai M, et al.

Association between sarcopenia and sleep disorder in older patients with diabetes. Bouchi R, Fukuda T, Takeuchi T, Minami I, Yoshimoto T, Ogawa Y.

Sarcopenia is associated with incident albuminuria in patients with type 2 diabetes: a retrospective observational study. J Diabetes Investig. Article CAS PubMed PubMed Central Google Scholar. Cheng Q, Hu J, Yang P, Cao X, Deng X, Yang Q, et al. Sarcopenia is independently associated with diabetic foot disease.

Sci Rep. Fukuda T, Bouchi R, Takeuchi T, Tsujimoto K, Minami I, Yoshimoto T, et al. Sarcopenic obesity assessed using dual energy X-ray absorptiometry DXA can predict cardiovascular disease in patients with type 2 diabetes: a retrospective observational study.

Cardiovasc Diabetol. Marra M, Sammarco R, De Lorenzo A, Iellamo F, Siervo M, Pietrobelli A, et al. Assessment of body composition in health and disease using bioelectrical impedance analysis BIA and dual energy X-ray absorptiometry DXA : a critical overview [Internet].

Hindawi; [cited Dec 18]. Ponti F, Santoro A, Mercatelli D, Gasperini C, Conte M, Martucci M, et al. Aging and imaging assessment of body composition: from fat to facts.

Front Endocrinol. Andreoli A, Scalzo G, Masala S, Tarantino U, Guglielmi G. Body composition assessment by dual-energy X-ray absorptiometry DXA. Radio Med Torino. Article CAS Google Scholar.

Park YW, Heymsfield SB, Gallagher D. Are dual-energy X-ray absorptiometry regional estimates associated with visceral adipose tissue mass? Int J Obes. Prior BM, Cureton KJ, Modlesky CM, Evans EM, Sloniger MA, Saunders M, et al.

In vivo validation of whole body composition estimates from dual-energy X-ray absorptiometry. J Appl Physiol. Salamone LM, Fuerst T, Visser M, Kern M, Lang T, Dockrell M, et al. Measurement of fat mass using DEXA: a validation study in elderly adults.

Prado CMM, Heymsfield SB. Lean tissue imaging. J Parenter Enter Nutr. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al. Bioelectrical impedance analysis—part I: review of principles and methods.

Clin Nutr. Houtkooper LB, Going SB, Lohman TG, Roche AF, Van Loan M. Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study. Lehrke M, Marx N. Diabetes mellitus and heart failure.

Am J Cardiol. Gillies PS, Dunn CJ. Drugs ;— Elmahal ME, Ramadan MM. Insulin-induced edema in a patient with type 2 diabetes mellitus.

Am J Case Rep. Metformin-SGLT2, dehydration, and acidosis potential. J Am Geriatr Soc. Stoner GD. Hyperosmolar hyperglycemic state. Am Fam Physician. PubMed Google Scholar. Ling CHY, de Craen AJM, Slagboom PE, Gunn DA, Stokkel MPM, Westendorp RGJ, et al.

Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population. Sartorio A, Malavolti M, Agosti F, Marinone PG, Caiti O, Battistini N, et al.

In the body, each metabolically active cell has an electrical potential difference of about mV at the cell membrane, and this potential permits the cell to act like a spherical condenser in an alternating electrical field.

Alternating current has a sinus wave, therefore the shift is measured in ° degrees and is described as a phase angle f phi or a alpha. To explain it in a more visual way - You will see a large phase angle for well nourished, "plump" cells with stabile membrane potentials, and comparable small phase angles with poorly nourished, "failing" cells that have low membrane potentials.

The phase angle, which is directly proportional to the BCM or body cell mass is of greatest significance at a 50 kHz frequency. Pure electrolyte water has a phase angle of 0 degrees, while a genuine cell membrane mass would have a phase angle of 90 degrees. Contrary to the cells of the BCM, fat cells have hardly any metabolic activity and cannot be detected by phase sensitive measurements because of their minimal membrane potential.

Fat cells are pure storage cells. The phase angle is used as a general measure of the membrane integrity of the cells. It provides information about the state of a cell and the overall condition of a patient's body, and as direct measurement parameter or "basic value", it is less prone to errors resulting from problems affected by measuring technology.

Multi-frequency measurements Frequency plays an important role in the resistance of a biological conductor, as for example very low ranging frequencies in the range 1 to 5 kHz Kilo Hertz have difficulties overcoming the cell membranes, and are therefore only able to reproduce in the extra-cellular mass, which means they practically hold no reactance component.

That's why, to be able to calculate the extra-cellular water ECW , there are multiple frequencies that can be used. As the frequency increases, so does the phase angle and with it the capacitive resistance reactance. The maximum frequency is reached at about 50 kHz.

Higher frequencies will cause both, the resistance and the reactance to decrease again. Cole defined this relationship between frequencies and resistances in , and the graphical representation of the correlation between resistance and reactance at different frequencies is called a Coleplot.

The use of multi-frequency analysis provides an improved differentiation with regard to cell loss or water displacement, by assessing variations in mass of the extra-cellular mass ECM and the body cell mass BCM. This process is especially beneficial in patients with a changed grade of hydration in the lean body mass, and patients with serious illness such as kidney or heart failure, or patients with edema and diseases that require the crucial monitoring of water balance dialysis, intravenous nutrition.

This multi-frequency analysis has many advantages. Resistance Inversely proportional to total body water, Resistance R is the pure resistance of a conductor to alternating current. Whereas fat mass has a raised resistance, lean body mass is a good conductor of electrical current, as proportionally it entails high amounts of water and electrolytes.

Perfusion and fluid content of the extremities therefore play an important role and explain the occasionally occurring over-proportional variations in resistance. They arise because of the influence of external conditions, such as ambient temperature and air-pressure, as well as internal factors such as for example congestion caused by illness and physical activity.

All of these conditions affect the water content of the extremities. This may also happen with very low water content of the extremities caused by high pressure or coldness.

The resistance measurement will be very much above the normal range with the result of this calculation method. The body water and therefore the lean body mass will tend to be too low and the body fat will be calculated as too high.

In another scenario, if the circulation in the extremities is increased or congested, the resistance shifts downwards. Body water and lean body mass appear too large, and calculations of the body fat will appear as too low in the results.

It is important to remember that the human body is never static, but functions with the help of a dynamic system, and that changes of the body water occur hourly and change on a daily basis. A current B. can therefore only be a snapshot of a dynamic system and of the condition at that point in time.

That's why several repeat and response measurements of the individual will provide a more accurate picture and improve the assessment of body composition. Reactance The resistance that a condenser exerts to an alternating current is called Reactance Xc.

Due to their protein-lipid layers, all cell membranes of the body act like mini-condensers and reactance therefore is an assessment of the body cell mass. General Principles Bioelectric impedance measurements BIM is the term representative for a variety of traditional and new noninvasive procedures and technologies that use electric current.

With the help of one or more surface electrodes, a tiny amount of electrical current is activated and is detected at surface electrodes placed elsewhere on the body, once the resultant electricity pulse has passed through.

As it quickly proceeds through the various physiological sections of the body, and passes through, a drop in voltage occurs. The current encounters impedance or resistance inherent in the fluids and tissues it passes through the various areas, among them the intracellular space, the lymphatic system, the bloodstream and others.

The drop in voltage delivers indirect information about the physical properties of the sections, where current has passed through. Alternating Current Bioelectric Impedance Analysis BIA : Among the various number of A. BIA models that are presently on the market, most are used for the obliquely measurement of total body water and to estimate the fat content of the body.

BIA, which uses alternating current A. as the most common form of testing, employs A. Various systems, varying broadly in complexity and design, operate with a wide range of intensities, frequencies and currents. For the patient, the amount of electricity delivered to the body is generally hard to even detect and far below any level that would result in cellular or tissue damage.

Once electric currents at or above 50 KHz are used, they flow non-selectively through extra cellular spaces as well as intracellular ones, as has been confirmed by various A. BIA studies. Once current has been sent to active tactile electrodes at a frequency at 50 KHz, its intensity enables the system to measure the reactance and resistance between 2 other passive tactile electrodes tetra-polar mode.

BIA and Its Calculated Parameters Total Body Water TBW Impedance measurements provide a quite accurate picture of electrolyte water contained in tissue.

Orally ingested water, which has not yet been absorbed by the body, is not measured; the same goes for ascites, because it is not part of the lean body mass. Administered solutions, however, are detected immediately. Lean Body Mass LBM The lean body mass is for the most part made up of inner organs, muscles, the skeletal system and the central nervous system, and refers to the tissue mass of the body that contains no fat.

These organ systems, although morphologically very different, contain matching functional structures. All of them contain matrix substance and extra-cellular fluids that support the metabolic exchange and assist in substrate transport and are made of cells that execute the synthesis and metabolism processes in the body.

In cases of for example edema or intensive car patients, where the quantity of lean body mass hydration is pathological, irregular calculations may be gathered for body cell mass, lean body mass, and extra-cellular mass - the secondary parameters - and will make the assessment of BIA measurements more difficult.

It helps in these cases, to look at the initial assessment and values for resistance, phase angle and reactance. The lean body mass contains of two subdivisions.

One is the body cell mass BCM, also referred to as the motor of the organism, and the other one is the connective tissues and transport medium, the extra-cellular mass ECM. Body Cell Mass BCM All tissue of the human organism entails to a certain degree Body cell mass, and the sum of all cells that are actively involved in the metabolic processes is called BCM.

While it is rather a functionally defined section and not so much an anatomically one above all, it consists all of the cells of the inner organs and muscles, with the muscles and the highest percentage to constitute the largest part of the BCM. Connective tissue with low fibrocyte content however only makes up a small percentage of the entire BCM, and adipocytes, due to their low energy metabolism are not at all considered being part of the BCM.

Consequently, the sum of adipocyte cells therefore forms its own compartment in the body. Included in the BCM are the following tissue forms: the smooth muscles, the cells of the skeletal muscle system, the inner organs, the cardiac muscles, the blood, the gastrointestinal tract, the nervous systems and the glands.

As all of the body's metabolic function is performed within the cells of the BCM, the BCM is the main specification for the analysis of a patient's nutritional state. It is also used as the standard specification for establishing the calorific requirement of the body and for the assessment of energy consumption.

In addition to the catabolism, the BCM also performs work on the anabolism including the keeping up of synthesis and cell structures for the ECM: For example the transportation proteins and enzymes, and the formation of connective tissue fibres, cartilage tissues and bones.

A person's body cell mass is a fractional constituent of the lean body mass, and a number of factors, such as age and physical condition or genetics constitution type play a role in the BCM that is available in an individual.

A higher percentage of body cell mass present in lean body mass is for example found in young people with high physical activity, such as competitive athletes. Their muscles are trained in the maturation phase of the body, and as a result, this higher proportion tends to be found in these individuals throughout their lives persistent hypertrophy of the muscle cells.

Age is also a factor in BCM. Older persons that are active, however, can retain their BCM to a large degree. These are optimal figures for BCM in the lean body mass. In view of the easy measuring methods for the assessment of the body composition, only phase sensitive BIA can be regarded to determine the BCM, and the maintenance of the BCM should be the main goal in any form of nutritional therapy.

A reduction of the body cell mass in BIA happens because of a genuine substantial loss of body cell mass, that can however also be accompanied by a temporary intracellular water loss. Extra-Cellular Mass ECM The extra-cellular mass ECM is the term for the lean body mass that exists outside the cells of the BCM.

Skin, elastin, collagen, tendons, bone and fasciae are the established connective tissue structures of the ECM, with the fluid parts consisting of plasma, interstitial and trans-cellular water.

Trans-cellular water is the description of fluids that are present in the body cavities, for example the contents of the gastro-intestinal lumen and the spinal fluid, while non-physiological trans-cellular fluids appear as ascites, or as pericardial or pleural effusions.

As approx. For example in an ascites of 5 litres, the trunk's resistance would only change by a few ohms, leaving the total resistance practically uninfluenced. Differences in fat mass that were brought about by weight changes generally appear without a change of resistance, hence the reason why BIA measurements are calculated as changes in fat mass, when it pertains to weight increases caused by ascites or pregnancy.

As the body cell mass BCM in healthy persons is always considerably larger than the extra-cellular mass ECM, resulting in an index that is smaller than 1. A decrease of BCM points to early stages of malnutrition.

The assessment of body composition has important ,ass in Natural Fat Burner evaluation BIA lean body mass evaluation rvaluation status and boyd potential health risks. Bioelectrical impedance evaluattion BIA boyd a valid method for amss BIA lean body mass evaluation of ,ass composition. BIA lean body mass evaluation is an alternative to Enhance your metabolism invasive and expensive methods like dual-energy X-ray absorptiometry, computerized tomography, and magnetic resonance imaging. Bioelectrical impedance analysis is an easy-to-use and low-cost method for the estimation of fat-free mass FFM in physiological and pathological conditions. The reliability of BIA measurements is influenced by various factors related to the instrument itself, including electrodes, operator, subject, and environment. BIA assumptions beyond its use for body composition are the human body is empirically composed of cylinders, FFM contains virtually all the water and conducting electrolytes in the body, and its hydration is constant. FFM can be predicted by BIA through equations developed using reference methods. Thank you for visiting nature. Mxss are using a browser evauation with Body cleanse for energy support for CSS. Body cleanse for energy evauation the best experience, we recommend you use a more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. A variety of easy-to-use commercial bioelectrical impedance appliances are available.

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However, this methodology has potential limitations resulting from the chemical composition of FFM i. Older adults with T2DM may have significant alterations in body fluids due to coexisting diabetes related complications such as heart failure [ 24 ]therapeutic agents [such as thiazolidinediones [ 25 ], insulin [ 26 ] and sodium-glucose cotransporter-2 SGLT-2 inhibitors [ 27 ] among others] and direct effects of hyperglycemia [ 28 ], which may potentially affect the validity of body composition assessment using BIA.

Previous studies assessed the validity of a commonly used direct segmental multi-frequency bioelectrical impendence analysis DSMF-BIA tool InBody analyzer in the general middle-aged adult population [ 29 ] as well as in obese middle-aged women [ 30 ].

However, to the best of our knowledge, no studies reported the validity of DSMF-BIA in older adults with T2DM.

A recent review paper published by Sbrignadello et al. Therefore, the aim of this study was to test the agreement between the DSMF-BIA and DXA in older adults with T2DM at baseline and during treatment with commonly used therapeutic interventions, which may affect body composition and body fluids including diet, exercise and empagliflozin.

The CEV study [ 32 ] took place at the institute of Endocrinology, Metabolism, and Hypertension IEMHTel-Aviv Sourasky Medical Center between May and February The study was approved by the Tel-Aviv Sourasky Medical Center Institutional Review Board. The present study is a post hoc analysis conducted in a population sampled from this study.

Over older adults with T2DM were screened according to the eligibility criteria described in [ 32 ]. Details of the full study design of the CEV study are available in [ 32 ] PRS: NCT Briefly, after screening and collection of baseline measurements, subjects were randomly allocated to a week intervention period in one of three groups: 1.

The final study population included older adults with T2DM 60 women. Eighty-four participants 49 women had a body composition assessment both by DXA; Lunar Prodigy, GE Healthcare, Madison, WI, USA and DSMF-BIA InBody body composition analyzer, Cerritos, CA, USA at baseline.

After 10 weeks of intervention 7 4 women10 5 women and 11 8 women participants had both measurements of DXA and DSMF-BIA in the CRT, diet or empagliflozin intervention groups, respectively.

DSMF-BIA: Measurements were obtained using a InBody body composition analyzer Cerritos, CA, USA in the standing position. DXA: DXA scan was performed using a Lunar Prodigy DXA scanner GE Healthcare, Madison, WI, USA. Scan modes thick, standard, or thin were automatically set by the software.

In addition to total-body composition, regional estimates were made for the arms, legs, and trunk. This was accomplished by manually adjusting cut positions for each region of interest ROI. A detailed list of the outcomes assessed in the CEV trial can be found in ref.

Height and waist circumference measured around the umbilicus were measured twice, and the average was then calculated, according to a standardized protocol.

Glycemic control was determined by fasting plasma glucose and HbA1c. Statistical analyses were performed using SPSS version We used two methods to evaluate the degree of agreement between the DXA indices and DSMF-BIA: 1 Bland—Altman plots; 2 the Intraclass Correlation Coefficient ICC.

We used a Bland—Altman plot with regression analysis, to show the differences between the indices, vs.

their mean. Sex stratified means were analyzed and the effect modification of sex for the agreement between the DSMF-BIA and the DXA was tested. Baseline subject characteristics are detailed in Table 1. Overall mean age was DSMF-BIA distribution is represented by the left box in each sub-figure; DXA distribution is represented by the right box in each sub-figure.

ASMI appendicular skeletal mass index, DSMF-BIA direct segmental multi-frequency bioelectrical impendence analysis, DXA dual-energy X-ray absorptiometry. The results of DSMF-BIA and DXA are shown in Table 2. Mean levels of lean mass segments significantly differed between the methods with a maximal difference of — 1.

Fat differences between the methods were significantly different with a maximal arm fat mass difference overestimated by 2. Sex was not found to be an effect modifier sex stratified mean levels of both lean and fat segments can be found in the supplementary file; Table S1. Examination of the agreement between the methods according to specific parameters of body composition are presented in Table 2Fig.

The degree of agreement was further tested using the Bland—Altman method Table 2Table S1Fig. Comparing the agreement between the methods on arms LBM showed a mean difference of 0.

For lean mass in the legs and trunk, as well as for ASMI, there was an agreement between the methods Fig. There was no agreement between the DSMF-BIA and the DXA methods for all fat measures except total fat percentage Table 2 and Fig. Total fat percentage bias was 1.

Agreement for total fat percentage remained for sex when analyzed separately Table S1 and Fig. Following 10 weeks of empagliflozin, CRT or a V-Med diet the trends for lean mass remained with arm LBM overestimated, legs LBM and ASMI underestimated, and fat percentage overestimated by the DSMF-BIA in all interventions Table 3 and Fig.

Despite having profound effects on body composition, the different interventions did not seem to affect the high agreement between DXA and DSMF-BIA. Bland—Altman plots presenting the difference between DSMF-BIA and DXA vs. The solid line represents the mean bias and the broken line the ±1.

Mean bias is considered the mean difference of all individuals between DSMF-BIA and DXA. ASMI appendicular skeletal mass index, DSMF-BIA direct segmental multi-frequency bioelectrical impendence analysis, DXA dual-energy X-ray absorptiometry, LBM lean body mass.

Our results clearly show that assessing body composition and diagnosing sarcopenia using the DSMF-BIA method is comparable to the DXA scan in older adults with T2DM. This was not affected by a week intervention period with treatment modalities often used in the treatment of T2DM.

The degree of agreement between the methods was overall better when comparing parameters of LBM than parameters of FM. For diagnosing sarcopenia in the clinical setting, DSMF-BIA had high specificity and high negative predictive value, suggesting it may be a useful screening tool for this condition.

Discrepancies between DXA and DSMF-BIA have been previously noted in different populations. This discrepancy highlights the importance of validation of DSMF-BIA in different populations and under different physiologic interventions.

Given the increasing rates of diabetes in general and in older adults in particular [ 2 ] and the wide use of BIA methods in studies testing diabetes and sarcopenia outcomes [ 31 ], it is not surprising that there was a call for validation studies testing the accuracy of BIA for this population [ 31 ].

Using DXA as a method to diagnose sarcopenia has several inherent limitations. DXA scan is less accessible and more expensive than DSMF-BIA. Very tall and very obese individuals cannot be adequately measured in a standard DXA machine and body thickness and hydration status e.

Moreover, to ensure the accuracy of any method for assessing muscle mass, standardization is needed. Calibration of materials and equations used to derive lean mass should be standardized across manufacturers. It is important to standardize the local regions of interest, such as trunk, arms, legs, which are different across manufacturers.

Finally, defining a reference population in the same way as has been achieved for the use of DXA in diagnosing osteoporosis should be considered [ 43 ]. The strengths of this manuscript include its relatively large population, its prospective nature and focus on a relatively poorly studied population of older adults with diabetes and low physical activity level.

Moreover, we present the lack of a significant effect of commonly used interventions for the treatment of T2DM on the validity of DSMF-BIA. Its weaknesses include the limited sample size in the prospective phase, the relatively short period of follow up and the fact that the study was not specifically designed to validate MF-BIA vs.

Also, the validity tested in the current paper is limited to relatively young older adults with T2DM who have limited rate of complications with low levels of sarcopenia. In that sense the significance of the findings presented here are important for early detecting lower muscle mass for early prevention, but with the cost of limited external validity.

: BIA lean body mass evaluation

Bioelectrical Impedance Analysis (BIA) and Body Composition Analyse - VitalScan In several clinical situations, i. Saladino, C. Bioelectrical impedance analysis in body composition measurement: National Institutes of Health Technology Assessment Conference Statement. Metformin-SGLT2, dehydration, and acidosis potential. et al. Nutrition ;17 7—8 —
Publication types Body cleanse for energy, C. Conclusions The studies presented BIA lean body mass evaluation eva,uation review demonstrate the metabolic and psychological bodh of understanding and treating Sports-specific diet plans eating disorder patients. Sarcopenic evxluation is associated with decreased survival and increased Promoting optimal colon function toxicity in Body cleanse for energy masw [ 5,6,7,8,9,10 ], whereas FFM loss is related to decreased survival, a negative clinical outcome, increased health care costs [ 2 ], and impaired overall health, functional capacities, and quality of life [ 4,5,6,7,8,9,10,11 ]. Paired t test was used to evaluate differences between BIA and DXA values. Undernutrition is insufficiently screened and treated in hospitalized or at-risk patients despite its high prevalence and negative impact on mortality, morbidity, length of stay LOSquality of life, and costs [ 1,2,3,4 ].
Bioelectrical Impedance Analysis (BIA) In vivo BIA lean body mass evaluation of whole body composition Red pepper BLT BIA lean body mass evaluation dual-energy X-ray absorptiometry. Sorry, a shareable link evalation not currently available for this evalaution. Fat Mass Indices FFMI and FMI Professor A. At hospital admission, body composition evaluation could be used for the detection of FFM loss and undernutrition. Soler-Cataluna JJ, Sanchez-Sanchez L, Martinez-Garcia MA, Sanchez PR, Salcedo E, Navarro M: Mid-arm muscle area is a better predictor of mortality than body mass index in COPD.
BIA lean body mass evaluation

Video

BODY FAT TEST Comparison: Hydrostatic, Skin Fold, DEXA Scan, BIA

BIA lean body mass evaluation -

FFM can be predicted by BIA through equations developed using reference methods. Several BIA prediction equations exist for the estimation of FFM, skeletal muscle mass SMM , or appendicular SMM. The BIA prediction models differ according to the characteristics of the sample in which they have been derived and validated in addition to the parameters included in the multiple regression analysis.

In choosing BIA equations, it is important to consider the characteristics of the sample in which it has been developed and validated, since, for example, age- and ethnicity-related differences could sensitively affect BIA estimates. Keywords: Bioelectrical impedance analysis; Body composition; Elderly; Prediction equations.

Abstract The assessment of body composition has important applications in the evaluation of nutritional status and estimating potential health risks.

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Sarcopenic obesity assessed using dual energy X-ray absorptiometry DXA can predict cardiovascular disease in patients with type 2 diabetes: a retrospective observational study.

Cardiovasc Diabetol. Marra M, Sammarco R, De Lorenzo A, Iellamo F, Siervo M, Pietrobelli A, et al. Assessment of body composition in health and disease using bioelectrical impedance analysis BIA and dual energy X-ray absorptiometry DXA : a critical overview [Internet].

Hindawi; [cited Dec 18]. Ponti F, Santoro A, Mercatelli D, Gasperini C, Conte M, Martucci M, et al. Aging and imaging assessment of body composition: from fat to facts.

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Radio Med Torino. Article CAS Google Scholar. Park YW, Heymsfield SB, Gallagher D. Are dual-energy X-ray absorptiometry regional estimates associated with visceral adipose tissue mass?

Int J Obes. Prior BM, Cureton KJ, Modlesky CM, Evans EM, Sloniger MA, Saunders M, et al. In vivo validation of whole body composition estimates from dual-energy X-ray absorptiometry. J Appl Physiol. Salamone LM, Fuerst T, Visser M, Kern M, Lang T, Dockrell M, et al.

Measurement of fat mass using DEXA: a validation study in elderly adults. Prado CMM, Heymsfield SB. Lean tissue imaging. J Parenter Enter Nutr. Kyle UG, Bosaeus I, De Lorenzo AD, Deurenberg P, Elia M, Gómez JM, et al.

Bioelectrical impedance analysis—part I: review of principles and methods. Clin Nutr. Houtkooper LB, Going SB, Lohman TG, Roche AF, Van Loan M. Bioelectrical impedance estimation of fat-free body mass in children and youth: a cross-validation study.

Lehrke M, Marx N. Diabetes mellitus and heart failure. Am J Cardiol. Gillies PS, Dunn CJ. Drugs ;— Elmahal ME, Ramadan MM. Insulin-induced edema in a patient with type 2 diabetes mellitus.

Am J Case Rep. Metformin-SGLT2, dehydration, and acidosis potential. J Am Geriatr Soc. Stoner GD. Hyperosmolar hyperglycemic state. Am Fam Physician. PubMed Google Scholar. Ling CHY, de Craen AJM, Slagboom PE, Gunn DA, Stokkel MPM, Westendorp RGJ, et al. Accuracy of direct segmental multi-frequency bioimpedance analysis in the assessment of total body and segmental body composition in middle-aged adult population.

Sartorio A, Malavolti M, Agosti F, Marinone PG, Caiti O, Battistini N, et al. Body water distribution in severe obesity and its assessment from eight-polar bioelectrical impedance analysis.

Eur J Clin Nutr. Sbrignadello S, Göbl C, Tura A. Bioelectrical impedance analysis for the assessment of body composition in sarcopenia and type 2 diabetes.

Buch A, Eldor R, Kis O, Keinan-Boker L, Dunsky A, Rubin A, et al. BMC Geriatr. American Diabetes Association. Executive summary: standards of medical care in diabetes Diabetes Care.

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Sarcopenia: European consensus on definition and diagnosis. Martin Bland J, Altman Douglas G. Statistical methods for assessing agreement between two methods of clinical measurement. Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research.

J Chiropr Med. Antonio J, Kenyon M, Ellerbroek A, Carson C, Burgess V, Tyler-Palmer D, et al. Comparison of dual-energy X-ray absorptiometry DXA versus a multi-frequency bioelectrical impedance InBody device for body composition assessment after a 4-week hypoenergetic diet.

J Funct Morphol Kinesiol. Article PubMed Central Google Scholar. Lahav Y, Goldstein N, Gepner Y. Comparison of body composition assessment across body mass index categories by two multifrequency bioelectrical impedance analysis devices and dual-energy X-ray absorptiometry in clinical settings.

McLester CN, Nickerson BS, Kliszczewicz BM, McLester JR. Reliability and agreement of various inbody body composition analyzers as compared to dual-energy X-ray absorptiometry in healthy men and women.

J Clin Densitom J Int Soc Clin Densitom. Hurt RT, Ebbert JO, Croghan I, Nanda S, Schroeder DR, Teigen LM, et al. The comparison of segmental multifrequency bioelectrical impedance analysis and dual-energy X-ray absorptiometry for estimating fat free mass and percentage body fat in an ambulatory population.

Writing Group for the ISCD Position Development Conference. Technical standardization for dual-energy x-ray absorptiometry.

Cadore EL, Izquierdo M. Exercise interventions in polypathological aging patients that coexist with diabetes mellitus: improving functional status and quality of life. Rahi B, Morais JA, Gaudreau P, Payette H, Shatenstein B. Energy and protein intakes and their association with a decline in functional capacity among diabetic older adults from the NuAge cohort.

Eur J Nutr. Older adults: standards of medical care in diabetes— Download references. This work was performed in partial fulfillment of the requirements for a Post-doctoral program by Assaf Buch at the Department of Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.

This work was not supported by any grant or external funding. InBody Co. Ltd did not support this study in any way and has not been involved in the initiation, preparation, and report of this study. Department of Nutritional Sciences, School of Health Sciences, Ariel University, Ariel, Israel.

Institute of Endocrinology, Metabolism, and Hypertension, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. Department of Medicine, Hadassah-Hebrew University Medical Center, Jerusalem, Israel.

Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel. Department of Human Movement Sciences, AgeAmsterdam, Amsterdam Movement Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Department of Medicine and Aged Care, AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia. Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.

The Sagol Center for Epigenetics of Metabolism and Aging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. You can also search for this author in PubMed Google Scholar. AB, RE, and NS were responsible for the study conception and design. AB, VR, EI, YG, and RE are responsible for ongoing study procedure.

AB and RE are responsible for data management. AB and RE are responsible for data analyses. AB, ABY, ABM, and RE wrote the manuscript. All authors critically reviewed the manuscript. Correspondence to Assaf Buch.

Open Access This article is licensed under a Creative Commons Attribution 4. Reprints and permissions. Buch, A. et al. Validation of a multi-frequency bioelectrical impedance analysis device for the assessment of body composition in older adults with type 2 diabetes. Diabetes 12 , 45 Download citation.

Received : 15 February Revised : 04 September Accepted : 28 September Published : 20 October Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content Thank you for visiting nature. Download PDF. Subjects Body mass index Geriatrics.

Abstract Background Aging and type 2 diabetes T2DM are associated with an increased risk of sarcopenia. Results The leg lean mass results according to DSMF-BIA and DXA were Conclusions In older adults with T2DM the degree of agreement between DSMF-BIA and DXA, was high, supporting the use of DSMF-BIA to measure muscle mass.

Background In western countries, the proportion of people over the age of 60 years is increasing faster than any other group [ 1 ].

Other relevant measurements and definitions A detailed list of the outcomes assessed in the CEV trial can be found in ref. Statistical methods Statistical analyses were performed using SPSS version Results General characteristics of the participants Baseline subject characteristics are detailed in Table 1.

Table 1 Data of the study participants for whom baseline measurements were performed on both DSMF-BIA and DXA. Full size table. Full size image. Table 2 Mean levels and agreement of body composition measures assessed by DSMF-BIA and DXA among older adults with T2DM.

Table 3 Agreement of body composition measures assessed by DSMF-BIA and DXA among older adults with T2DM—after 10 weeks of V-MED, CRT, or empagliflozin. Discussion Our results clearly show that assessing body composition and diagnosing sarcopenia using the DSMF-BIA method is comparable to the DXA scan in older adults with T2DM.

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Article CAS Google Scholar Park YW, Heymsfield SB, Gallagher D. Article Google Scholar Prior BM, Cureton KJ, Modlesky CM, Evans EM, Sloniger MA, Saunders M, et al. Article CAS PubMed Google Scholar Salamone LM, Fuerst T, Visser M, Kern M, Lang T, Dockrell M, et al.

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Journal of Intensive BIIA volume Free-range poultryArticle number: 61 Cite this article. Metrics details. Skeletal Body cleanse for energy atrophy commonly mads in critically ill patients, and decreased muscle mass is associated with worse clinical outcomes. Muscle mass can be assessed using various tools, including ultrasound and bioelectrical impedance analysis BIA. However, the effectiveness of muscle mass monitoring is unclear in critically ill patients.

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