Guidance for assessment of the muscle mass phenotypic criterion for the Global Leadership Initiative on Malnutrition (GLIM) diagnosis of malnutrition
Open accessAbstract
The Global Leadership Initiative on Malnutrition (GLIM) provides consensus criteria for the diagnosis of malnutrition that can be widely applied. The GLIM approach is based on the assessment of three phenotypic (weight loss, low body mass index, and low skeletal muscle mass) and two etiologic (low food intake and presence of disease with systemic inflammation) criteria, with diagnosis confirmed by any combination of one phenotypic and one etiologic criterion fulfilled. Assessment of muscle mass is less commonly performed than other phenotypic malnutrition criteria, and its interpretation may be less straightforward, particularly in settings that lack access to skilled clinical nutrition practitioners and/or to body composition methodologies. In order to promote the widespread assessment of skeletal muscle mass as an integral part of the GLIM diagnosis of malnutrition, the GLIM consortium appointed a working group to provide consensus-based guidance on assessment of skeletal muscle mass. When such methods and skills are available, quantitative assessment of muscle mass should be measured or estimated using dual-energy x-ray absorptiometry, computerized tomography, or bioelectrical impedance analysis. For settings where these resources are not available, then the use of anthropometric measures and physical examination are also endorsed. Validated ethnic- and sex-specific cutoff values for each measurement and tool are recommended when available. Measurement of skeletal muscle function is not advised as surrogate measurement of muscle mass. However, once malnutrition is diagnosed, skeletal muscle function should be investigated as a relevant component of sarcopenia and for complete nutrition assessment of persons with malnutrition.
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Assessment of body composition and muscle function can provide useful information to guide the clinical management of obesity.
“Assessment of body composition (lean/muscle mass and fat mass) and muscle function can provide useful information to guide the clinical management of obesity.”
From Strategies for minimizing muscle loss during use of incretin‐mimetic drugs for treatment of obesity (2025) · cites this paper as [110]
Section 3.3.1.1 recommends investigating skeletal muscle mass when low muscle function is detected, especially in people with overweight or obesity, and says function measures may help assess nutrition treatment. The paper’s guidance concerns malnutrition assessment; it does not establish that measuring fat mass or these measures together guides the broader clinical management of obesity. Page numbers were not available in the indexed passages. (LLM, conf=0.84)
Experimental — accuracy not yet measuredMRI can be considered a gold-standard method for accuracy, but MRI is not routinely available for assessment of muscle mass.
“Magnetic resonance imaging (MRI) can be considered a gold‐standard method for accuracy, 42 but MRI is not routinely available for the assessment of muscle mass. 40 , 41 , 42”
From GLIM consensus approach to diagnosis of malnutrition: A 5‐year update (2025) · cites this paper as [40]
Section 3.1.4.2 says MRI is unlikely to be available for routine clinical practice, supporting the availability claim. However, section 3.1.1.3 says that no criterion-standard or superior technique is currently acknowledged, so the paper does not support calling MRI a gold standard for accuracy. Page numbers were not available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredA GLIM working group later published guidance on how to measure muscle mass and define low muscle mass.
“For this reason, a GLIM working group later published such guidance. 40 , 41”
From GLIM consensus approach to diagnosis of malnutrition: A 5‐year update (2025) · cites this paper as [40]
The guidance papers clarified that low muscle strength, although often closely associated with loss of muscle mass and included in full nutrition assessment after malnutrition diagnosis, is not a component of the GLIM diagnostic algorithm.
“The guidance papers clarified that low muscle strength, although often closely associated with loss of muscle mass and included in full nutrition assessment after malnutrition diagnosis, is not a component of the GLIM diagnostic algorithm. 40 , 41”
From GLIM consensus approach to diagnosis of malnutrition: A 5‐year update (2025) · cites this paper as [40]
When machine-based techniques are not available or by regional preference, physical examination or standard anthropometric measures such as calf circumference or mid-arm muscle circumference may be used to evaluate muscle mass.
“When not available or by regional preference, physical examination or standard anthropometric measures such as calf circumference or mid‐arm muscle circumference may be used.”
From GLIM consensus approach to diagnosis of malnutrition: A 5‐year update (2025) · cites this paper as [40]
Calf circumference may be considered in the absence of machine-based techniques to evaluate muscle mass, and clinical judgment of inflammatory disease burden may only require laboratory confirmation (by CRP) in cases of uncertainty.
“Two GLIM working groups have since provided more detailed guidance; ie, calf circumference may be considered in the absence of machine‐based techniques to evaluate muscle mass, 40 , 41 and clinical judgment of inflammatory disease burden may only require laboratory confirmation (by CRP) in cases of uncertainty. 59 , 60”
From GLIM consensus approach to diagnosis of malnutrition: A 5‐year update (2025) · cites this paper as [40]
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References 80 · Cited by 406
Research works printed but not linked: 1
- [64]64. Clark RV, Walker AC, O'Connor-Semmes RL, Leonard MS, Miller RR, Stimpson SA, et al. Total body skeletal muscle mass: estimation by cre- atine (methyl-d3) dilution in humans. J Appl Physiol 2014;116(12): 1605e13.
- Authors
- Barazzoni, R., Jensen, G. L., Correia, M. I. T. D., Gonzalez, M. C., Higashiguchi, T., Shi, H. P., Bischoff, S. C., Boirie, Y., Carrasco, F., Cruz-Jentoft, A., Fuchs-Tarlovsky, V., Fukushima, R., Heymsfield, S., Mourtzakis, M., Muscaritoli, M., Norman, K., Nyulasi, I., Pisprasert, V., Prado, C., De van der Schueren, M., Yoshida, S., Yu, J., Cederholm, T., & Compher, C.
- Affiliations
- University of Trieste (IT)
- University of Vermont (US)
- University of Hohenheim (DE)
- Instituto Ramón y Cajal de Investigación Sanitaria (ES)
- Teikyo Heisei University (JP)
- University of Waterloo (CA)
- Sapienza University of Rome (IT)
- Humboldt-Universität zu Berlin (DE)
- La Trobe University (AU)
- Khon Kaen University (TH)
- University of Alberta (CA)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Uppsala University (SE)
- University of Pennsylvania (US)
- Corresponding author
- Barazzoni, Rocco
- ORCID
- Barazzoni, Rocco
- Jensen, Gordon L.
- Bischoff, Stephan C.
- Boirie, Yves
- Carrasco, Fernando
- Cruz-Jentoft, Alfonso
- Fuchs-Tarlovsky, Vanessa
- Fukushima, Ryoji
- Heymsfield, Steve
- Mourtzakis, Marina
- Muscaritoli, Maurizio
- Norman, Kristina
- Nyulasi, Ibolya
- Pisprasert, Veeradej
- Prado, Carla
- De van der Schueren, Marian
- Yoshida, Sadao
- Yu, Jianchun
- Cederholm, Tommy
- Compher, Charlene
- Venue
- Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 41
- Issue
- 6
- Pages
- 1425-1433
- ISSN
- 0261-5614 (ISSN-L)
- OpenAlex
- W4224210638
- Semantic Scholar
- 09954afc19b25ce8b168a44e5ab771e3d7077cbe
- Cited by
- 406
- References
- 80
- Citations by year
- 2026: 96 · 2025: 117 · 2024: 95 · 2023: 72 · 2022: 25
- FWCI
- 47.84
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Clinical Nutrition (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion)
- HAL (submittedVersion, cc-by-nc-nd)
- ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion, cc-by-nc-nd)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Nutrition and Health in Aging
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Nursing › Nutrition and Dietetics › Clinical Nutrition and Gastroenterology
- Keywords
- malnutrition diagnosis, GLIM criteria, skeletal muscle mass, muscle mass assessment, anthropometric measures, body composition, dual-energy X-ray absorptiometry, bioelectrical impedance analysis, computed tomography, cut-off values, sarcopenia, muscle function testing, nutritional assessment
- MeSH terms
- Female, Humans, Leadership, Male, Mitral Valve Prolapse, Myopia, Nutritional Status, Skin Diseases, Weight Loss, Nutrition Assessment, Muscle, Skeletal, Malnutrition
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