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Vol. 6 No. 1 (2026): Volume 6, Issue 1, Year 2026

Articles

Identification of Risk Factors through Anthropometric Assessment in Institutionalized Adolescents: Beyond BMI

  • Célica Mendoza Cañamar,
  • María Elena Villarreal Arce
Célica Mendoza Cañamar
Universidad de Monterrey, Nuevo León, México.
María Elena Villarreal Arce
Universidad de Monterrey, Nuevo León, México.
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DOI: https://doi.org/10.34256/ijk26110

Published 19-04-2026

Keywords

  • ISAK,
  • BMI,
  • Anthropometry,
  • Adolescents

How to Cite

Cañamar, C. M., & Villarreal Arce, M. E. (2026). Identification of Risk Factors through Anthropometric Assessment in Institutionalized Adolescents: Beyond BMI. International Journal of Kinanthropometry, 6(1), 86–92. https://doi.org/10.34256/ijk26110

Copyright (c) 2026 Célica Mendoza Cañamar, María Elena Villarreal Arce

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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Abstract

Introduction: Malnutrition during adolescence poses a public health challenge, manifesting as underweight, excess body fat, and alterations in muscle mass indicators that are not identifiable using the Body Mass Index (BMI). It is necessary to incorporate more comprehensive indicators to enable a more precise detection of cardiovascular risk, obesity, and malnutrition. Methods: A cross-sectional study was conducted involving 53 adolescents (23 males and 30 females) aged 11 to 17, residing in a social welfare institution in Nuevo León, Mexico. The ISAK protocol was employed. Indicators such as BMI, fat mass index, estimated muscle mass, and the waist-to-hip ratio were calculated. Data were analyzed using the ISAK Metry software. Results: Most of the adolescents were classified as having normal weight according to BMI; however, 28.3% were identified as being at cardiometabolic risk based on waist and hip circumference measurements. Nineteen adolescents were identified as having extreme values ​​regarding muscle mass and/or body fat levels, and 12 normal-weight adolescents were found to have alterations in muscle mass and/or body fat indicators. Significant correlations were observed among skinfolds, BMI, circumferences, and body weight (p < 0.05). Conclusion: More comprehensive assessment profiles succeed in identifying higher risks among adolescents; therefore, standardized measurements conducted according to the ISAK protocol in vulnerable populations—facilitate timely diagnosis.

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References

  1. Aceves-Martins, M., Llaurado, E., Tarro, L., Sola, R., Giralt, M. (2016). Obesity-promoting factors in Mexican children and adolescents: Challenges and opportunities. Global Health Action, 9(1), 29626. https://doi.org/10.3402/gha.v9.29625
  2. Ashwell, M., Gibson, S. (2016). Waist-to-height ratio as an indicator of ‘early health risk’: Simpler and more predictive than using a ‘matrix’ based on BMI and waist circumference. BMJ Open, 6(3), e010159. https://doi.org/10.1136/bmjopen-2015-010159
  3. Caleyachetty, R., Thomas, G.N., Kengne, A.P., Echouffo-Tcheugui, J.B., Schilsky, S., Khodabocus, J., Uauy, R. (2018). The double burden of malnutrition among adolescents: analysis of data from the Global School-Based Student Health and Health Behavior in School-Aged Children surveys in 57 low- and middle-income countries. The American Journal of Clinical Nutrition, 108(2), 414.424, https://doi.org/10.1093/ajcn/nqy105
  4. Costa-Urrutia, P., Vizuet-Gámez, A. Ramírez-Alcántara, M., Guillén-González, M., Medina-Contreras, O., Valdés-Moreno, M. Musalem-Younes, C., Solares-Tlapechco, J., Granados, J., Franco-Trecu, V., Rodríguez-Arellano, M. (2019). Obesity measured as percent body fat and its relationship with Body Mass Index, and percentile curves for Mexican pediatric population. PLoS ONE, 14(2), e0212792. https://doi.org/10.1371/journal.pone.0212792.
  5. De Lorenzo, A., Martinoli, R., Vaia, F., Di Renzo, L. (2016). Normal weight obese (NWO) women: An evaluation of a candidate new syndrome. Nutrition, Metabolism and Cardiovascular Diseases, 16(8), 513–523. https://doi.org/10.1016/j.numecd.2005.10.010
  6. Frisancho, A. R. (1990). Anthropometric standards for the assessment of growth and nutritional status. University of Michigan Press. https://doi.org/10.3998/mpub.12198
  7. Gibson, R.S. (2005). Principles of nutritional assessment (2nd ed.). Oxford University Press. https://doi.org/10.1093/oso/9780195171693.001.0001
  8. Higuera-Domínguez, F., Ochoa-Díaz-López, H., Irecta-Nájera, C. Nuñez-Ortega, P., Castro-Quezada, I., García-Miranda, R., Solís-Hernández, R., García-Parra, E., Ruiz-López, M. (2025). Impacto f early childhood malnutrition on cardiometabolic risk factors in young adults from Marginalized Areas of Chiapas, Mexico. Nutrients, 17(2). https://doi.org/10.3390/nu17020254.
  9. Popkin, B.M., Corvalan, C., Grummer-Strawn, L.M. (2020). Dynamics of the double burden of malnutrition and the changing nutrition reality. The Lancet, 395(10217), 65–74. https://doi.org/10.1016/S0140-6736(19)32497-3
  10. Santiago-Arango, M., Pérez-Campos, E., Porras-Chaparro, I., Ruiz-Rosado, J., Cabrera-Fuentes, H., Mayoral, E., Martínez-Cruz, M., Hernández-Huerta, M., Mayoral, L. (2025). Agreement on BMI classification in Mexican children and adolescentes using different references. Nutrients, 17(3). https://doi.org/10.3390/nu17030587.
  11. Wells, J.C.K. (2014). Toward body composition reference data for infants, children, and adolescents. Advances in Nutrition, 5(3), 320S–329S. https://doi.org/10.3945/an.113.005371
  12. World Health Organization (WHO). (2007). Growth reference data for 5–19 years. WHO. https://www.who.int/tools/growth-reference-data-for-5to19-years
  13. Zárate-Ortiz, A., Melse-Boonstra, A. Rodríguez-Ramírez, S., Hernández-Cordero, S., Feskens, E. (2019). Dietary patterns and the double burden of malnutrition in Mexican adolescents : Results from ENSANUT-2006. Nutrients. 11(11). https://doi.org/10.3390/nu11112753