journal article·2026-01-14Open access

The Seven Methods for the Evaluation of Nutritional Status—ABCDEFG: Narrative Review

Raynier Zambrano-Villacres, Cecilia Arteaga-Pazmiño, Washington David Guevara Castillo, Maria Elisa Herrera-Fontana, Lorena Daniela Domínguez Brito, Luis Miguel Becerra Granados, Paulo E. Recoba-Obregón, Dolores Rodríguez-Veintimilla, Viviana Bressi, Derly Andrade-Molina, Evelyn Frias-Toral, Samuel Duran-Aguero

Applied Sciences· Volume 16· Issue 2

Abstract

Background: Nutritional status assessment is the cornerstone of the Nutrition Care Process, guiding diagnosis, intervention, and monitoring. The classical ABCD model (Anthropometry, Biochemical, Clinical, Dietary) has been widely applied; however, it presents limitations in addressing current nutritional and epidemiological challenges. Objective: This narrative review aims to synthesize and update the scientific evidence on the expanded nutritional assessment model, known as ABCDEFG, which incorporates the Ecological–microbiota (E), Functional (F), and Genomic–nutrigenomic (G) approaches. Methods: A narrative review of the literature was conducted through PubMed, Scopus, and Web of Science, covering publications from 2013 to 2025. Articles were selected based on relevance to at least one of the seven assessment domains. Findings were synthesized descriptively and critically, highlighting applications, strengths, and limitations. Results: The ABCDEFG framework offers a multidimensional perspective of nutritional assessment. While anthropometric, biochemical, clinical, and dietary methods remain essential, the inclusion of ecological dimensions (gut microbiota, environmental influences), functional measures (e.g., muscle strength, physical performance), and genomics enables a more sensitive and personalized evaluation. This integrative approach supports better clinical decision-making and research innovation in nutrition and health sciences. Conclusions: The seven-method model broadens the scope of nutritional assessment, bridging traditional and emerging tools. Its application enhances the capacity to identify nutritional risks, design targeted interventions, and advance precision nutrition.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Nutrition, Genetics, and Disease · Nutrition, Health, and Society Studies · Dietetics, Nutrition, and Education

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Dirección de Investigación, Universidad ECOTEC, Km.13.5 Samborondon, Samborondón 092302, Ecuador

Doctorado en Ciencias Biomédicas, Escuela de Medicina y Ciencias de la Salud, Instituto Universitario Italiano de Rosario (IUNIR), Rosario S2000CTT, Argentina

Carrera de Nutrición y Dietética, Facultad de Ciencias Médicas, Universidad de Guayaquil, Guayaquil 090613, Ecuador

Escuela de Nutriologia, Facultad de Ciencias Médicas, de la Salud y la Vida, Universidad Internacional del Ecuador, Quito 170411, Ecuador

Carrera de Nutrición y Dietética, Escuela de Salud Pública, Universidad San Francisco de Quito, Quito 170901, Ecuador

Grupo de Investigación Nutrición Dietética, Biotecnología y Análisis de Alimentos (GINDBA), Universidad Estatal de Milagro, Milagro 091050, Ecuador

Departamento de Alimentación y Nutrición, Facultad de Salud, Universidad Javeriana, Cali 110231, Colombia

Carrera de Nutrición y Dietética, Facultad de Nutrición y Dietética, Universidad Científica del Sur, Lima 15073, Peru

Grupo Especializado de Nutrición del Perú (GENUP), Lima 15073, Peru

Clinical Nutrition Service-SOLCA, Guayaquil 090505, Ecuador

OMICS Science Laboratory, Faculty of Health Science, Universidad Espíritu Santo, Samborondón 0901952, Ecuador

School of Medicine, Universidad Espíritu Santo, Samborondón 0901952, Ecuador

Division of Research, Texas State University, 601 University Dr, San Marcos, TX 78666, USA

Escuela de Nutrición y Dietética, Facultad de Ciencias de la Rehabilitación y Calidad de Vida, Universidad San Sebastián, Providencia 7500000, Chile

Funding

ECOTEC University

References (100+)

Show source-provided references
1. Nutrition Care Process: Elements for its implementation and use by Nutrition and Dietetics Professionals10.14306/renhyd.24.2.961 ↗
2. Nutritional care process model: Consensus for Latin America
3. Update of the Clinical Nutritionist Role: Standards of Practice10.4067/s0717-75182021000300437 ↗
4. The Double Burden of Malnutrition in Individuals: Identifying Key Challenges and Re-Thinking Research Focus10.1111/nbu.12670 ↗
5. Phillips, M.E., Robertson, M.D., Bennett-Eastley, K., Rowe, L., Frampton, A.E., and Hart, K.H. (2024). Standard Nutritional Assessment Tools Are Unable to Predict Loss of Muscle Mass in Patients Due to Undergo Pancreatico-Duodenectomy: Highlighting the Need for Detailed Nutritional Assessment. Nutrients, 16.10.3390/nu16091269 ↗
6. Morphofunctional Assessment of Patient’s Nutritional Status: A Global Approach
7. Considerations for Anthropometry Specific to People with Disproportionate Short Stature10.1007/s12325-024-03061-y ↗
8. Kinanthropometry and Body Composition: A Natural Home for Three-Dimensional Photonic Scanning10.1080/02640411003661304 ↗
9. Ros, F.E., Vaquero-Cristóbal, R., and Marfell-Jones, M. (2019). Protocolo Internacional Para la Valoración Antropométrica, 2019, ISAK. Sociedad Internacional para el Avance de la Cineantropometría.
10. Marfell-Jones, M., Vaquero-Cristóbal, R., and Ros, F.E. (2024). ISAK Accreditation Handbook (2024), International Society for the Advancement of Kinanthropometry (ISAK).
11. Exploring Body Composition and Somatotype Profiles among Youth Professional Soccer Players10.3233/MNM-240038 ↗
12. Esparza, M., Vaquero, R., Castillo, A., Ponce, F., Mecherques, M., and Baglietto, N. (2025, June 08). ISAK Metry 2025. Available online: https://isakmetry.com/.
13. Martínez-Mireles, X., Nava-González, E.J., López-Cabanillas Lomelí, M., Puente-Hernández, D.S., Gutiérrez-López, M., Lagunes-Carrasco, J.O., López-García, R., and Ramírez, E. (2025). The Shape of Success: A Scoping Review of Somatotype in Modern Elite Athletes Across Various Sports. Sports, 13.10.3390/sports13020038 ↗
14. Concordance between Muscle Ultrasound and Bioelectrical Impedance Analysis for Muscle Assessment in Gastric Cancer Patients: A Prospective Study10.1016/j.clnesp.2025.07.634 ↗
15. The Role of Muscle Ultrasound to Predict Sarcopenia10.1016/j.nut.2022.111692 ↗
16. Reliability and Validity of Quadriceps Muscle Thickness Measurements in Ultrasonography: A Comparison with Muscle Mass and Strength10.2490/prm.20230008 ↗
17. Zanotelli, A., Rossi, A.P., Del Monte, L., Vantini, G., Stabile, G., Urbani, S., Giani, A., Zoico, E., Babbanini, A., and Fantin, F. (2024). The Role of Combined Muscle Ultrasound and Bioimpedentiometry Parameters for Sarcopenia Diagnosis in a Population of Hospitalized Older Adults. Nutrients, 16.10.3390/nu16152429 ↗
18. The Use of Bioelectrical Impedance Vector Analysis for a Nutritional Evaluation of Older Adults in the Community10.1016/j.exger.2021.111276 ↗
19. Body Composition Assessment Using Bioelectrical Impedance Analysis (BIA) in a Wide Cohort of Patients Affected with Mild to Severe Obesity10.1016/j.clnu.2021.04.033 ↗
20. Keller, U. (2019). Nutritional Laboratory Markers in Malnutrition. J. Clin. Med., 8.10.3390/jcm8060775 ↗
21. Inflammation and Response to Nutrition Interventions10.1002/jpen.2534 ↗
22. Continuous Glucose Monitoring in a Healthy Population: Understanding the Post-Prandial Glycemic Response in Individuals without Diabetes Mellitus10.1016/j.metabol.2023.155640 ↗
23. Picó, C., Serra, F., Rodríguez, A.M., Keijer, J., and Palou, A. (2019). Biomarkers of Nutrition and Health: New Tools for New Approaches. Nutrients, 11.10.3390/nu11051092 ↗
24. Use of Urine Electrolytes and Urine Osmolality in the Clinical Diagnosis of Fluid, Electrolytes, and Acid-Base Disorders10.1016/j.ekir.2021.02.003 ↗
25. Approaches to Setting Dietary Reference Values for Micronutrients, and Translation into Recommendations10.1017/S0029665121000562 ↗
26. Biomarkers in Nutritional Epidemiology: Applications, Needs and New Horizons10.1007/s00439-009-0662-5 ↗
27. Parámetros bioquímicos básicos, hematológicos y hormonales para el control de la salud y el estado nutricional en los deportistas10.14306/renhyd.18.3.24 ↗
28. Role of the Nutrition-focused Physical Examination in Identifying Malnutrition and Its Effectiveness10.1002/ncp.10797 ↗
29. Anthropometric indexes and cardiovascular risk in Ecuadorian university students: A comparison with international references
30. Reber, E., Gomes, F., Vasiloglou, M.F., Schuetz, P., and Stanga, Z. (2019). Nutritional Risk Screening and Assessment. J. Clin. Med., 8.10.3390/jcm8071065 ↗
31. Cutaneous Signs of Nutritional Deficiencies10.1007/s13670-024-00425-8 ↗
32. From Kwashiorkor to Edematous Malnutrition10.1007/s13312-017-1171-6 ↗
33. Kolarš, B., Mijatović Jovin, V., Živanović, N., Minaković, I., Gvozdenović, N., Dickov Kokeza, I., and Lesjak, M. (2025). Iron Deficiency and Iron Deficiency Anemia: A Comprehensive Overview of Established and Emerging Concepts. Pharmaceuticals, 18.10.3390/ph18081104 ↗
34. Iron Deficiency in Infancy and Neurocognitive and Educational Outcomes in Young Adulthood10.1037/dev0001030 ↗
35. Vitamin A Deficiency Disorders in Children and Women10.1177/15648265030244S204 ↗
36. Vitamin A Supplementation for Preventing Morbidity and Mortality in Children from Six Months to Five Years of Age
37. Alberts, A., Moldoveanu, E.-T., Niculescu, A.-G., and Grumezescu, A.M. (2025). Vitamin C: A Comprehensive Review of Its Role in Health, Disease Prevention, and Therapeutic Potential. Molecules, 30.10.3390/molecules30030748 ↗
38. Dietary Vitamin C in Human Health10.1016/bs.afnr.2017.11.006 ↗
39. The Good, the Bad, and the Ugly of Calcium Supplementation: A Review of Calcium Intake on Human Health10.2147/CIA.S157523 ↗
40. Calcium Intake and Metabolism in Infants and Young Children: A Systematic Review of Balance Studies for Supporting the Development of Calcium Requirements10.1093/advances/nmac003 ↗
41. Fleet, J. (2022). Vitamin D-Mediated Regulation of Intestinal Calcium Absorption. Nutrients, 14.10.3390/nu14163351 ↗
42. Eidelberg, A., and Newberry, C. (2022). Dietary Composition and Nutritional Deficiencies. Nutrition, Weight, and Digestive Health, The Clinician’s Desk Reference, Springer.10.1007/978-3-030-94953-2_2 ↗
43. Utilization of Nutrition-Focused Physical Assessment in Identifying Micronutrient Deficiencies10.1177/0884533615573054 ↗
44. Hamilton, C., Jevenn, A., Hipskind, P., Galand, M., and Pogatschnik, C. (2022). Nutrition-Focused Physical Exam for Adults: An Illustrated Handbook, American Society for Parenteral and Enteral Nutrition (ASPEN). [2nd ed.].
45. Utilidad del CANs SCORE para valoración clínica del estado nutricional del recién nacido10.47993/gmb.v44i1.215 ↗
46. Bates, C., Bogin, B., and Holmes, B. (2017). Nutritional Assessment Methods. Human Nutrition, Oxford University Press.
47. Dietary Assessment Toolkits: An Overview10.1017/S1368980018002951 ↗
48. Métodos de evaluación de la ingesta actual: Registro o diario diétetico
49. FAO (2018). Dietary Assessment: A Resource Guide to Method Selection and Application in Low Resource Settings, Food and Agriculture Organization of the United Nations. Available online: https://www.fao.org/4/i0351e/i0351e12.pdf.
50. Food Frequency Questionnaires
51. The Dietary History as a Tool in Research10.1016/S0002-8223(21)43949-0 ↗
52. What and How Much Do We Eat? 24-Hour Dietary Recall Method
53. Accuracy in the Estimation of Food Servings against the Portions in Food Photographs10.1038/sj.ejcn.1602758 ↗
54. Portion Size Estimation in Dietary Assessment: A Systematic Review of Existing Tools, Their Strengths and Limitations10.1093/nutrit/nuz107 ↗
55. (2019). Manual Fotografico de Porciones Para Cuantificacion Alimentaria—Ecuador, USFQ-Press.
56. Herrera, M.E., Chisaguano, M., Rodríguez, G.V., and Crispim, S.P. (2022). Manual Fotográfico de Porciones Para Cuantificación Alimentaria del Ecuador, USFQ Press. [2nd ed.].
57. Ortiz, J., Rubio, G., Donoso, S., and Ochoa-Avilés, A. (2018). Tabla de Composición de Alimentos, Cuenca—Ecuador 2018, Universidad de Cuenca.
58. (2021). Tabla de Composición Química de los Alimentos: Basada en Nutrientes de Interés Para la Población Ecuatoriana, USFQ Press.
59. D’Alessandro, C., Benedetti, A., Di Paolo, A., Giannese, D., and Cupisti, A. (2022). Interactions between Food and Drugs, and Nutritional Status in Renal Patients: A Narrative Review. Nutrients, 14.10.3390/nu14010212 ↗
60. Drug–Nutrient Interactions: A Broad View with Implications for Practice10.1016/j.jada.2011.09.002 ↗
61. Impact of Drug Nutrient Interaction on Chronic Disease: Roles of Pharmacy, Nursing, Nutrition|Migration Letters
62. Dragan, S., Man, D., and Kundnani, N.R. (2025). Nutrient-Drug Interactions and Cardiotoxicity in Oncologic Patients. Cardiovascular Toxicity, Springer.10.1007/978-3-031-90598-8_19 ↗
63. Food-Drug Interactions: Implications for Nursing Practice
64. Systems to Model the Personalized Aspects of Microbiome Health and Gut Dysbiosis10.1016/j.mam.2022.101115 ↗
65. Bioinformatic Methodologies in Assessing Gut Microbiota10.3390/microbiolres15040170 ↗
66. (2025, October 23). Babraham Bioinformatics. FastQC. Available online: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/.
67. Trimmomatic: A Flexible Trimmer for Illumina Sequence Data10.1093/bioinformatics/btu170 ↗
68. The SILVA Ribosomal RNA Gene Database Project: Improved Data Processing and Web-Based Tools10.1093/nar/gks1219 ↗
69. An Improved Greengenes Taxonomy with Explicit Ranks for Ecological and Evolutionary Analyses of Bacteria and Archaea10.1038/ismej.2011.139 ↗
70. GTDB: An Ongoing Census of Bacterial and Archaeal Diversity through a Phylogenetically Consistent, Rank Normalized and Complete Genome-Based Taxonomy10.1093/nar/gkab776 ↗
71. Prodan, A., Tremaroli, V., Brolin, H., Zwinderman, A.H., Nieuwdorp, M., and Levin, E. (2020). Comparing Bioinformatic Pipelines for Microbial 16S rRNA Amplicon Sequencing. PLoS ONE, 15.10.1371/journal.pone.0227434 ↗
72. METAnnotatorX2: A Comprehensive Tool for Deep and Shallow Metagenomic Data Set Analyses10.1128/mSystems.00583-21 ↗
73. Tools for Analysis of the Microbiome10.1007/s10620-020-06091-y ↗
74. Integrating Taxonomic, Functional, and Strain-Level Profiling of Diverse Microbial Communities with bioBakery 310.7554/eLife.65088 ↗
75. Predictive Functional Profiling of Microbial Communities Using 16S rRNA Marker Gene Sequences10.1038/nbt.2676 ↗
76. Kers, J.G., and Saccenti, E. (2022). The Power of Microbiome Studies: Some Considerations on Which Alpha and Beta Metrics to Use and How to Report Results. Front. Microbiol., 12.10.3389/fmicb.2021.796025 ↗
77. Mensah, G., Maseng, M., Allard, S., and Gilbert, J. (2024). The Microbiome, Metabolism, and Networks in Precision Nutrition. Precision Nutrition, Academic Press.10.1016/B978-0-443-15315-0.00011-0 ↗
78. Nayman, E., Schwartz, B., Polanco, F., Firek, A., Gumabong, A., Hofstee, N., Narasimhan, G., Cickovski, T., and Mathee, K. (2023). Microbiome Depiction through User-Adapted Bioinformatic Pipelines and Parameters. J. Med. Microbiol., 72.10.1099/jmm.0.001756 ↗
79. Balmant, B.D., Fonseca, D.C., Rocha, I.M., Callado, L., Torrinhas, R.S.M.d.M., and Waitzberg, D.L. (2023). Dys-R Questionnaire: A Novel Screening Tool for Dysbiosis Linked to Impaired Gut Microbiota Richness. Nutrients, 15.10.3390/nu15194261 ↗
80. The Healthy Human Microbiome10.1186/s13073-016-0307-y ↗
81. Shifting the Balance: Antibiotic Effects on Host-Microbiota Mutualism10.1038/nrmicro2536 ↗
82. Kase, B.E., Liese, A.D., Zhang, J., Murphy, E.A., Zhao, L., and Steck, S.E. (2024). The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota. Nutrients, 16.10.3390/nu16071045 ↗
83. Construcción y validación de un cuestionario para medir función gastrointestinal en adultos
84. Prevalencia del riesgo de desnutrición y situación de la terapia nutricional en pacientes adultos hospitalizados en Perú10.35454/rncm.v3n2.28 ↗
85. The Impact of Pelvic Radiotherapy on the Gut Microbiome and Its Role in Radiation-Induced Diarrhoea: A Systematic Review10.1186/s13014-021-01899-y ↗
86. National Cancer Institute (2025, October 23). National Cancer Institute’s Common Terminology Criteria for Adverse Events: Diarrheaa, Available online: https://www.ncbi.nlm.nih.gov/books/NBK65768.4/table/CDR0000062736__287/?report=objectonly.
87. Barry, D.J., Wu, S.S.X., and Cooke, M.B. (2024). The Relationship Between Gut Microbiota, Muscle Mass and Physical Function in Older Individuals: A Systematic Review. Nutrients, 17.10.3390/nu17010081 ↗
88. Understanding the Gut Microbiota and Sarcopenia: A Systematic Review10.1002/jcsm.12784 ↗
89. A Critical Analysis of Eating Disorders and the Gut Microbiome10.1186/s40337-022-00681-z ↗
90. Gut Microbiota-Derived Metabolites as Central Regulators in Metabolic Disorders10.1136/gutjnl-2020-323071 ↗
91. Chen, Y., Xu, J., and Chen, Y. (2021). Regulation of Neurotransmitters by the Gut Microbiota and Effects on Cognition in Neurological Disorders. Nutrients, 13.10.3390/nu13062099 ↗
92. Ruiz-Pozo, V., Tamayo-Trujillo, R., Cadena-Ullauri, S., Frias-Toral, E., Guevara-Ramírez, P., Paz-Cruz, E., Chapela, S., Montalván, M., Morales-López, T., and Simancas-Racines, D. (2023). The Molecular Mechanisms of the Relationship between Insulin Resistance and Parkinson’s Disease Pathogenesis. Nutrients, 15.10.3390/nu15163585 ↗
93. The Gut-Liver Axis and Gut Microbiota in Health and Liver Disease10.1038/s41579-023-00904-3 ↗
94. Nutritional Guidelines for the Management of Insulin Resistance10.1080/10408398.2021.1908223 ↗
95. Endocrinologist’s Crucial Role in Metabolic Dysfunction-Associated Steatotic Liver Disease: A Comprehensive Review
96. Nutritional Strategies for Battling Obesity-Linked Liver Disease: The Role of Medical Nutritional Therapy in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) Management10.1007/s13679-024-00597-6 ↗
97. Buchynskyi, M., Kamyshna, I., Halabitska, I., Petakh, P., Kunduzova, O., Oksenych, V., and Kamyshnyi, O. (2025). Unlocking the Gut-Liver Axis: Microbial Contributions to the Pathogenesis of Metabolic-Associated Fatty Liver Disease. Front. Microbiol., 16.10.3389/fmicb.2025.1577724 ↗
98. Gut Microbiota as a Transducer of Dietary Cues to Regulate Host Circadian Rhythms and Metabolism10.1038/s41575-021-00452-2 ↗
99. The Impact of a Western Diet on Gut Microbiota and Circadian Rhythm: A Comprehensive Systematic Review of in Vivo Preclinical Evidence10.1016/j.lfs.2024.122741 ↗
100. Reytor-González, C., Simancas-Racines, D., Román-Galeano, N.M., Annunziata, G., Galasso, M., Zambrano-Villacres, R., Verde, L., Muscogiuri, G., Frias-Toral, E., and Barrea, L. (2025). Chrononutrition and Energy Balance: How Meal Timing and Circadian Rhythms Shape Weight Regulation and Metabolic Health. Nutrients, 17.10.3390/nu17132135 ↗