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How to calculate Lean Body Mass (LBM)BIA lean body mass evaluation -
In addition, the accuracy of the clinical screening of undernutrition could be limited at hospital admission. Indeed, patients with undernutrition may have the same BMI as sex- and age-matched healthy controls but a significantly decreased FFM hidden by an expansion of the FM and the total body water which can be measured by bioelectrical impedance analysis BIA [ 13 ].
This example illustrates that body composition evaluation allows a more accurate identification of FFM loss than body weight loss or BMI decrease. The lack of sensitivity and specificity of weight, BMI, and percentage of weight loss argue for the need for other methods to evaluate the nutritional status.
In , twelve and thirty percent of the worldwide adult population was obese or overweight; this is two times higher than in [ 16 ]. The prevalence of overweight and obesity is also increasing in hospitalized patients.
The BMI increase masks undernutrition and FFM loss at hospital admission. Sarcopenic obesity is characterized by increased FM and reduced FFM with a normal or high body weight. The emergence of the concept of sarcopenic obesity will increase the number of situations associated with a lack of sensitivity of the calculations of BMI and body weight change for the early detection of FFM loss.
This supports a larger use of body composition evaluation for the assessment and follow-up of nutritional status in clinical practice fig. Body composition evaluation is a valuable technique to assess nutritional status.
Firstly, it gives an evaluation of nutritional status through the assessment of FFM. Secondly, by measuring FFM and phase angle with BIA, it allows evaluation of the disease prognosis and outcome.
Body composition evaluation allows measurement of the major body compartments: FFM including bone mineral tissue , FM, and total body water. Table 2 shows indicative values of the body composition of a healthy subject weighing 70 kg.
In several clinical situations, i. At hospital admission, body composition evaluation could be used for the detection of FFM loss and undernutrition. Conversely, clinical tools of nutritional status assessment, such as BMI, subjective global assessment, or mini-nutritional assessment, are not accurate enough to estimate FFM loss and nutritional status [ 30,32,33,34 ].
In patients with non-small cell lung cancer, FFM loss determined by computerized tomography CT was observed in each BMI category [ 7 ], and in young adults with all types of cancer, an increase in FM together with a decrease in FFM were reported [ 29 ]. These findings reveal the lack of sensitivity of BMI to detect FFM loss.
In COPD, the assessment of FFM by BIA is a more sensitive method to detect undernutrition than anthropometry [ 33,35 ]. BIA is also more accurate at assessing nutritional status in children with severe neurologic impairment than the measurement of skinfold thickness [ 36 ].
Mean values of body composition compartments adapted from Pichard and Kyle [ 19 and Wang et al. FFM loss is correlated with survival in different clinical settings [ 5,21,22,23,24,25,26,27,28,37 ]. In patients with amyotrophic lateral sclerosis, an FM increase, but not an FFM increase, measured by BIA, was correlated with survival during the course of the disease [ 28 ].
The relation between body composition and mortality has not yet been demonstrated in the intensive care unit. The relation between body composition and mortality has been demonstrated with anthropometric methods, BIA, and CT.
Measurement of the mid-arm muscle circumference is an easy tool to diagnose sarcopenia [ 38 ]. The mid-arm muscle circumference has been shown to be correlated with survival in patients with cirrhosis [ 39,40 ], HIV infection [ 41 ], and COPD in a stronger way than BMI [ 42 ].
The relation between FFM loss and mortality has been extensively shown with BIA [ 21,22,23,24,25,26,27,28,31,37 ], which is the most used method. Recently, very interesting data suggest that CT could evaluate the disease prognosis in relation to muscle wasting. In obese cancer patients, sarcopenia as assessed by CT measurement of the total skeletal muscle cross-sectional area is an independent predictor of the survival of patients with bronchopulmonary [ 5,7 ], gastrointestinal [ 5 ], and pancreatic cancers [ 6 ].
FFM assessed by measurement of the mid-thigh muscle cross-sectional area by CT is also predictive of mortality in COPD patients with severe chronic respiratory insufficiency [ 43 ]. In addition to mortality, a low FFMI at hospital admission is significantly associated with an increased LOS [ 3,44 ].
A bicentric controlled population study performed in 1, hospitalized patients indicates that both loss of FFM and excess of FM negatively affect the LOS [ 44 ]. Patients with sarcopenic obesity are most at risk of increased LOS.
This study also found that excess FM reduces the sensitivity of BMI to detect nutritional depletion [ 44 ]. Together with the observation that the BMI of hospitalized patients has increased during the last decade [ 17 ], these findings suggest that FFM and FFMI measurement should be used to evaluate nutritional status in hospitalized patients.
BIA measures the phase angle [ 45 ]. The phase angle threshold associated with reduced survival is variable: less than 2. The phase angle is also associated with the severity of lymphopenia in AIDS [ 56 ], and with the risk of postoperative complications among gastrointestinal surgical patients [ 57 ].
The relation of phase angle with prognosis and disease severity reinforces the interest in using BIA for the clinical management of patients with chronic diseases at high risk of undernutrition and FFM loss. In summary, FFM loss or a low phase angle is related to mortality in patients with chronic diseases, cancer including obesity cancer patients , and elderly patients in long-stay facilities.
A low FFM and an increased FM are associated with an increased LOS in adult hospitalized patients. The relation between FFM loss and clinical outcome is clearly shown in patients with sarcopenic obesity. In these patients, as the sensitivity of BMI for detecting FFM loss is strongly reduced, body composition evaluation appears to be the method of choice to detect undernutrition in routine practice.
Overall, the association between body composition, phase angle, and clinical outcome reinforces the pertinence of using a body composition evaluation in clinical practice. Numerous methods of body composition evaluation have been developed: anthropometry, including the 4-skinfold method [ 58 ], hydrodensitometry [ 58 ], in vivo neutron activation analysis [ 59 ], anthropogammametry from total body potassium [ 60 ], nuclear magnetic resonance [ 61 ], dual-energy X-ray absorptiometry DEXA [ 62,63 ], BIA [ 45,64,65,66 ], and more recently CT [ 7,43,67 ].
DEXA, BIA, and CT appear to be the most convenient methods for clinical practice fig. Compared with other techniques of body composition evaluation, the lack of reproducibility and sensitivity of the 4-skinfold method limits its use for the accurate measurement of body composition in clinical practice [ 33,34 ].
However, in patients with cirrhosis [ 39,40 ], COPD [ 34 ], and HIV infection [ 41 ], measurement of the mid-arm muscle circumference could be used to assess sarcopenia and disease-related prognosis.
DEXA allows noninvasive direct measurement of the three major components of body composition. The measurement of bone mineral tissue by DEXA is used in clinical practice for the diagnosis and follow-up of osteoporosis.
As the clinical conditions complicated by osteoporosis are often associated with undernutrition, i. elderly women, patients with organ insufficiencies, COPD [ 68 ], inflammatory bowel diseases, and celiac disease, DEXA could be of the utmost interest for the follow-up of both osteoporosis and nutritional status.
However, the combined evaluation of bone mineral density and nutritional status is difficult to implement in clinical practice because the reduced accessibility of DEXA makes it impossible to be performed in all nutritionally at-risk or malnourished patients. The principles and clinical utilization of BIA have been largely described in two ESPEN position papers [ 45,66 ].
BIA is based on the capacity of hydrated tissues to conduct electrical energy. The measurement of total body impedance allows estimation of total body water by assuming that total body water is constant. From total body water, validated equations allow the calculation of FFM and FM [ 69 ], which are interpreted according to reference values [ 70 ].
BIA is the only technique which allows calculation of the phase angle, which is correlated with the prognosis of various diseases.
BIA equations are valid for: COPD [ 65 ]; AIDS wasting [ 71 ]; heart, lung, and liver transplantation [ 72 ]; anorexia nervosa [ 73 ] patients, and elderly subjects [ 74 ].
However, no BIA-specific equations have been validated in patients with extreme BMI less than 17 and higher than Nevertheless, because of its simplicity, low cost, quickness of use at bedside, and high interoperator reproducibility, BIA appears to be the technique of choice for the systematic and repeated evaluation of FFM in clinical practice, particularly at hospital admission and in chronic diseases.
Finally, through written and objective reports, the wider use of BIA should allow improvement of the traceability of nutritional evaluation and an increase in the recognition of nutritional care by the health authorities.
Recently, several data have suggested that CT images targeted on the 3rd lumbar vertebra L3 could strongly predict whole-body fat and FFM in cancer patients, as compared with DEXA [ 7,67 ]. Interestingly, the evaluation of body composition by CT presents great practical significance due to its routine use in patient diagnosis, staging, and follow-up.
The muscles included in the calculation of the muscle cross-sectional area are psoas, paraspinal muscles erector spinae, quadratus lumborum , and abdominal wall muscles transversus abdominis, external and internal obliques, rectus abdominis [ 6 ].
CT also provided detail on specific muscles, adipose tissues, and organs not provided by DEXA or BIA. L3-targeted CT images could be theoretically performed solely, since they result in X-ray exposition similar to that of a chest radiography.
In summary, DEXA, BIA, and L3-targeted CT images could all measure body composition accurately. The technique selection will depend on the clinical context, hardware, and knowledge availability. Body composition evaluation by DEXA should be performed in patients having a routine assessment of bone mineral density.
Also, analysis of L3-targeted CT is the method of choice for body composition evaluation in cancer patients. Body composition evaluation should also be done for every abdominal CT performed in patients who are nutritionally at risk or undernourished.
Because of its simplicity of use, BIA could be widely implemented as a method of body composition evaluation and follow-up in a great number of hospitalized and ambulatory patients. Future research will aim to determine whether a routine evaluation of body composition would allow early detection of the increased FFM catabolism related to critical illness [ 75 ].
The evaluation of FFM could be used for the calculation of energy needs, thus allowing the optimization of nutritional intakes according to nutritional needs. This could be of great interest in specific situations, such as severe neurologic disability, overweight, and obesity.
In 61 children with severe neurologic impairment and intellectual disability, an equation integrating body composition had good agreement with the doubly labeled water method. It gave a better estimation of energy expenditure than did the Schofield predictive equation [ 36 ].
However, in 9 anorexia nervosa patients with a mean BMI of In overweight or obese patients, the muscle catabolism in response to inflammation was the same as that observed in patients with normal BMI.
Indeed, despite a higher BMI, the FFM of overweight or obese individuals is similar or slightly increased to that of patients with normal BMI. Thus, the use of actual weight for the assessment of the energy needs of obese patients would result in overfeeding and its related complications.
Thus, follow-up of FFM by BIA could help optimize nutritional intakes when indirect calorimetry cannot be performed. Body composition evaluation allows a qualitative assessment of body weight variations. Body composition evaluation could be used for the follow-up of healthy elderly subjects [ 90 ].
Body composition evaluation allows characterization of the increase in body mass in terms of FFM and FM [ 81,91 ]. After hematopoietic stem cell transplantation, the increase in BMI is the result of the increase in FM, but not of the increase in FFM [ 81 ].
By identifying the patients gaining weight but reporting no or insufficient FFM, body composition evaluation could contribute to influencing the medical decision of continuing nutritional support that would have been stopped in the absence of body composition evaluation.
In summary, body composition evaluation is of the utmost interest for the follow-up of nutritional support and its impact on body compartments. This point has been recently illustrated in oncology patients with sarcopenic obesity.
FFM loss was determined by CT as described above. In cancer patients, some therapies could affect body composition by inducing muscle wasting [ 92 ]. In turn, muscle wasting in patients with BMI less than 25 was significantly associated with sorafenib toxicity in patients with metastatic renal cancer [ 8 ].
In metastatic breast cancer patients receiving capecitabine treatment, and in patients with colorectal cancer receiving 5-fluoro-uracile, using the convention of dosing per unit of body surface area, FFM loss was the determinant of chemotherapy toxicity [ 9,10 ] and time to tumor progression [ 10 ].
In colorectal cancer patients administered 5-fluoro-uracil, low FFM is a significant predictor of toxicity only in female patients [ 9 ].
The variation in toxicity between women and men may be partially explained by the fact that FFM was lower in females. Indeed, FFM represents the distribution volume of most cytotoxic chemotherapy drugs. In 2, cancer patients, the individual variations in FFM could change by up to three times the distribution volume of the chemotherapy drug per body area unit [ 5 ].
Thus, administering the same doses of chemotherapy drugs to a patient with a low FFM compared to a patient with a normal FFM would increase the risk of chemotherapy toxicity [ 5 ].
These data suggest that FFM loss could have a direct impact on the clinical outcome of cancer patients. These findings justify the systematic evaluation of body composition in all cancer patients in order to detect FFM loss, tailor chemotherapy doses according to FFM values, and then improve the efficacy-tolerance and cost-efficiency ratios of the therapeutic strategies [ 93 ].
corticosteroids, immunosuppressors infliximab, azathioprine or methotrexate , or sedatives propofol. In summary, measurement of FFM should be implemented in cancer patients treated with chemotherapy.
Clinical studies are needed to demonstrate the importance of measuring body composition in patients treated with other medical treatments. The implementation of body composition evaluation in routine care presents a challenge for the next decades. Indeed the concomitant increases in elderly subjects and patients with chronic diseases and cancer, and in the prevalence of overweight and obesity in the population, will increase the number of patients nutritionally at risk or undernourished, particularly those with sarcopenic obesity.
Body composition evaluation should be used to improve the screening of undernutrition in hospitalized patients. The results could be expressed according to previously described percentiles of healthy subjects [ 95,96 ].
Body composition evaluation should be performed at the different stages of the disease, during the course of treatments and the rehabilitation phase. BIA, L3-targeted CT, and DEXA represent the techniques of choice to evaluate body composition in clinical practice fig.
In the setting of cost-effective and pragmatic use, these three techniques should be alternatively chosen. In cancer, undernourished, and nutritionally at-risk patients, an abdominal CT should be completed by the analysis of L3-targeted images for the evaluation of body composition.
In other situations, BIA appears to be the simplest most reproducible and less expensive method, while DEXA, if feasible, remains the reference method for clinical practice. By allowing earlier management of undernutrition, body composition evaluation can contribute to reducing malnutrition-induced morbidity and mortality, improving the quality of life and, as a consequence, increasing the medico-economic benefits fig.
The latter needs to be demonstrated. Moreover, based on a more scientific approach, i. allowing for printing reports, objective initial assessment and follow-up of nutritional status, and the adjustment of drug doses, body composition evaluation would contribute to a better recognition of the activities related to nutritional evaluation and care by the medical community, health care facilities, and health authorities fig.
Screening of undernutrition is insufficient to allow for optimal nutrition care. This is in part due to the lack of sensitivity of BMI and weight loss for detecting FFM loss in patients with chronic diseases. Methods of body composition evaluation allow a quantitative measurement of FFM changes during the course of disease and could be used to detect FFM loss in the setting of an objective, systematic, and early undernutrition screening.
FFM loss is closely related to impaired clinical outcomes, survival, and quality of life, as well as increased therapy toxicity in cancer patients. Thus, body composition evaluation should be integrated into clinical practice for the initial assessment, sequential follow-up of nutritional status, and the tailoring of nutritional and disease-specific therapies.
Body composition evaluation could contribute to strengthening the role and credibility of nutrition in the global medical management, reducing the negative impact of malnutrition on the clinical outcome and quality of life, thereby increasing the overall medico-economic benefits.
Thibault and C. Pichard are supported by research grants from the public foundation Nutrition Plus. Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Annals of Nutrition and Metabolism.
Advanced Search. Skip Nav Destination Close navigation menu Article navigation. Volume 60, Issue 1. Rationale for a New Strategy for the Screening of Undernutrition. Body Composition Evaluation for the Assessment of Nutritional Status.
Body Composition Evaluation for the Calculation of Energy Needs. Body Composition Evaluation for the Follow-Up and Tailoring of Nutritional Support.
Body Composition Evaluation for Tailoring Medical Treatments. Towards the Implementation of Body Composition Evaluation in Clinical Practice. Disclosure Statement.
Article Navigation. Review Articles December 16 The Evaluation of Body Composition: A Useful Tool for Clinical Practice Subject Area: Endocrinology , Further Areas , Nutrition and Dietetics , Public Health.
Ronan Thibault ; Ronan Thibault. a Centre de Recherche en Nutrition Humaine Auvergne, UMR Nutrition Humaine, INRA, Clermont Université, Service de Nutrition Clinique, CHU de Clermont-Ferrand, Clermont-Ferrand, France;.
This Site. Google Scholar. Claude Pichard Claude Pichard. b Nutrition Unit, Geneva University Hospital, Geneva, Switzerland. Ann Nutr Metab 60 1 : 6— Article history Received:. Cite Icon Cite.
toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. View large Download slide. Table 1 Main reasons for the lack of nutritional screening at hospitals. View large. View Large. Table 2 Mean values of body composition compartments adapted from Pichard and Kyle [ 19 and Wang et al.
Ronan Thibault and Claude Pichard declare no conflict of interest. Pirlich M, Schutz T, Norman K, Gastell S, Lübke HJ, Bischoff SC, Bolder U, Frieling T, Güldenzoph H, Hahn K, Jauch KW, Schindler K, Stein J, Volkert D, Weimann A, Werner H, Wolf C, Zürcher G, Bauer P, Lochs H: The German hospital malnutrition study.
Clin Nutr ;— Amaral TF, Matos LC, Tavares MM, Subtil A, Martins R, Nazaré M, Sousa Pereira N: The economic impact of disease-related malnutrition at hospital admission. Pichard C, Kyle UG, Morabia A, Perrier A, Vermeulen B, Unger P: Nutritional assessment: lean body mass depletion at hospital admission is associated with increased length of stay.
Am J Clin Nutr ;— Capuano G, Gentile PC, Bianciardi F, Tosti M, Palladino A, Di Palma M: Prevalence and influence of malnutrition on quality of life and performance status in patients with locally advanced head and neck cancer before treatment. Support Care Cancer ;— Prado CM, Lieffers JR, McCargar LJ, Reiman T, Sawyer MB, Martin L, Baracos VE: Prevalence and clinical implications of sarcopenic obesity in patients with solid tumours of the respiratory and gastrointestinal tracts: a population-based study.
Lancet Oncol ;— Tan BHL, Birdsell LA, Martin L, Baracos VE, Fearon KC: Sarcopenia in an overweight or obese patient is an adverse prognostic factor in pancreatic cancer. Clin Cancer Res ;— Baracos VE, Reiman T, Mourtzakis M, Gioulbasanis I, Antoun S: Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis.
Am J Clin Nutr ;91 suppl : S—S. Antoun S, Baracos VE, Birdsell L, Escudier B, Sawyer MB: Low body mass index and sarcopenia associated with dose-limiting toxicity of sorafenib in patients with renal cell carcinoma.
Ann Oncol ;— Prado CM, Baracos VE, McCargar LJ, Mourtzakis M, Mulder KE, Reiman T, Butts CA, Scarfe AG, Sawyer MB: Body composition as an independent determinant of 5-fluorouracil-based chemotherapy toxicity.
Prado CM, Baracos VE, McCargar LJ, Reiman T, Mourtzakis M, Tonkin K, Mackey JR, Koski S, Pituskin E, Sawyer MB: Sarcopenia as a determinant of chemotherapy toxicity and time to tumor progression in metastatic breast cancer patients receiving capecitabine treatment.
Hofhuis JG, Spronk PE, van Stel HF, Schrijvers GJ, Rommes JH, Bakker J: The impact of critical illness on perceived health-related quality of life during ICU treatment, hospital stay, and after hospital discharge: a long-term follow-up study. Chest ;— Guest JF, Panca M, Baeyens JP, de Man F, Ljungqvist O, Pichard C, Wait S, Wilson L: Health economic impact of managing patients following a community-based diagnosis of malnutrition in the UK.
Kyle UG, Morabia A, Slosman DO, Mensi N, Unger P, Pichard C: Contribution of body composition to nutritional assessment at hospital admission in patients: a controlled population study.
Br J Nutr ;— Kondrup J, Allison SP, Elia M; Vellas B, Plauth M: Educational and Clinical Practice Committee, European Society of Parenteral and Enteral Nutrition ESPEN : ESPEN guidelines for nutrition screening Haute Autorité de Santé: IPAQSS: informations.
World Health Organization: Obesity and overweight: fact sheet No. Thibault R, Chikhi M, Clerc A, Darmon P, Chopard P, Picard-Kossovsky M, Genton L, Pichard C: Assessment of food intake in hospitalised patients: a 10 year-comparative study of a prospective hospital survey.
Stenholm S, Harris TB, Rantanen T, Visser M, Kritchevsky SB, Ferrucci L: Sarcopenic obesity: definition, cause and consequences. Curr Opin Clin Nutr Metab Care ;— It's also wise to understand that there is more to health than your body fat percentage or weight, and these scales are only a tool, not a reflection of your general wellness.
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Leab you BIA lean body mass evaluation visiting nature. You Relaxing herbal alternative using lesn browser version with limited support for Lexn. To obtain the best experience, we recommend you use a more up to date BI 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. The aim of this study was to examine the usefulness of a commercially available body composition meter using bioelectrical impedance analysis BIA by comparing its measurement results with those obtained from dual-energy X-ray absorptiometry DXA. The assessment of body masz has important applications in the evaluation of nutritional status BBIA estimating potential BIA lean body mass evaluation risks. Bioelectrical impedance analysis Evaluatuon is a obdy method Bodj the assessment of body composition. BIA is an bofy to more invasive and Digestive health recipes Healthy blood circulation like dual-energy X-ray lan, 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.
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