OVERWEIGHT AND CARDIOMETABOLIC RISK - BEYOND BODY MASS INDEX
Keywords:
overweight, obesity, cardiometabolic risk, body mass index, anthropometric measures.Abstract
Overweight and obesity represent a significant public health problem and are associated with an increased risk of metabolic and cardiovascular diseases. Cardiometabolic risk is determined not only by the amount of body mass, but also by the distribution and functional characteristics of adipose tissue, with particular importance of central and visceral fat accumulation. Objective: To summarize the current scientific evidence on the use of body mass index and additional anthropometric indicators in the assessment of overweight, obesity and their associated cardiometabolic risk. Methodology: A review of scientific publications, systematic reviews, meta-analyses and current scientific opinions identified through the databases PubMed/MEDLINE, Scopus and Web of Science was performed. Data on body mass index, waist circumference, waist-hip ratio, waist-height ratio, body fatness index, body shape index and methods for assessing body composition were analyzed. Results: Body mass index remains an important and widely used primary screening tool, but it does not adequately reflect body composition and fat distribution. Waist circumference and waist-to-height ratios provide additional information on central fat accumulation and are associated with cardiometabolic risk assessment. Waist-to-hip ratio contribute to the assessment of fat distribution, while body fatness index and body shape index expand the possibilities for characterizing body shape and central adiposity. Body composition assessment methods complement anthropometric assessment by providing information on fat and lean body mass and fat distribution. Conclusion: Using body mass index as a stand-alone indicator does not provide a sufficiently complete characterization of cardiometabolic risk. Recommendations: A comprehensive assessment is recommended, combining BMI with indicators of central fat accumulation and, if necessary, with methods for assessing body composition. Such an approach allows for a more complete characterization of the anthropometric profile and its associated health risk.
References
Busetto, L., Dicker, D., Frühbeck, G., Halford, J. C. G., Sbraccia, P., Yumuk, V., & Goossens, G. H. (2024). A new framework for the diagnosis, staging and management of obesity in adults. Nature medicine, 30(9), 2395–2399. https://doi.org/10.1038/s41591-024-03095-3
Chamarthi, V. S., & Daley, S. F. (2025). Secondary Causes of Obesity and Comprehensive Diagnostic Evaluation. In StatPearls. StatPearls Publishing.
Dagenais, G. R., Yi, Q., Mann, J. F., Bosch, J., Pogue, J., & Yusuf, S. (2005). Prognostic impact of body weight and abdominal obesity in women and men with cardiovascular disease. American heart journal, 149(1), 54–60. https://doi.org/10.1016/j.ahj.2004.07.009
Després J. P. (2012). Body fat distribution and risk of cardiovascular disease: an update. Circulation, 126(10), 1301–1313. https://doi.org/10.1161/CIRCULATIONAHA.111.067264
Faria, S. L., Faria, O. P., Cardeal, M. D., & Ito, M. K. (2014). Validation study of multi-frequency bioelectrical impedance with dual-energy X-ray absorptiometry among obese patients. Obesity surgery, 24(9), 1476–1480. https://doi.org/10.1007/s11695-014-1190-5
Fu H, Liu H, Han Y, Wang T, Yu J, Liu W, Liu Z, Hu X, Shen Z and Gao Y (2026) Risk association and diagnostic value of body roundness index for cardiovascular-kidney-metabolic-related outcomes: a systematic review and meta-analysis. Front. Endocrinol. 17:1814762. doi: 10.3389/fendo.2026.1814762
Fuchs, A., Samovski, D., Smith, G. I., Cifarelli, V., Farabi, S. S., Yoshino, J., Pietka, T., Chang, S. W., Ghosh, S., Myckatyn, T. M., & Klein, S. (2021). Associations Among Adipose Tissue Immunology, Inflammation, Exosomes and Insulin Sensitivity in People With Obesity and Nonalcoholic Fatty Liver Disease. Gastroenterology, 161(3), 968–981.e12. https://doi.org/10.1053/j.gastro.2021.05.008
GBD 2021 Adolescent BMI Collaborators (2025). Global, regional, and national prevalence of child and adolescent overweight and obesity, 1990-2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021. Lancet (London, England), 405(10481), 785–812. https://doi.org/10.1016/S0140-6736(25)00397-6
GBD 2021 Risk Factors Collaborators (2024). Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet (London, England), 403(10440), 2162–2203. https://doi.org/10.1016/S0140-6736(24)00933-4
Heymsfield, S. B. (2025). Advances in body composition: a 100-year journey. International Journal of Obesity, 49(2), 177-181.
Jacobs, E. J., Newton, C. C., Wang, Y., Patel, A. V., McCullough, M. L., Campbell, P. T., Thun, M. J., & Gapstur, S. M. (2010). Waist circumference and all-cause mortality in a large US cohort. Archives of internal medicine, 170(15), 1293–1301. https://doi.org/10.1001/archinternmed.2010.201
Ji, M., Zhang, S., & An, R. (2018). Effectiveness of A Body Shape Index (ABSI) in predicting chronic diseases and mortality: a systematic review and meta-analysis. Obesity reviews : an official journal of the International Association for the Study of Obesity, 19(5), 737–759. https://doi.org/10.1111/obr.12666
Krakauer, N. Y., & Krakauer, J. C. (2012). A new body shape index predicts mortality hazard independently of body mass index. PloS one, 7(7), e39504. https://doi.org/10.1371/journal.pone.0039504
Lee, M. J., Wu, Y., & Fried, S. K. (2010). Adipose tissue remodeling in pathophysiology of obesity. Current opinion in clinical nutrition and metabolic care, 13(4), 371–376. https://doi.org/10.1097/MCO.0b013e32833aabef
Li, H., Zhang, J., Wang, H., & Luo, L. (2025). Association between body roundness index and metabolic syndrome in middle-aged and older adults: a prospective cohort study in China. Frontiers in public health, 13, 1604593. https://doi.org/10.3389/fpubh.2025.1604593
Liu, C., Wong, P. Y., Chung, Y. L., Chow, S. K., Cheung, W. H., Law, S. W., Chan, J. C. N., & Wong, R. M. Y. (2023). Deciphering the "obesity paradox" in the elderly: A systematic review and meta-analysis of sarcopenic obesity. Obesity reviews : an official journal of the International Association for the Study of Obesity, 24(2), e13534. https://doi.org/10.1111/obr.13534
Mongraw-Chaffin, M., Allison, M. A., Burke, G. L., Criqui, M. H., Matsushita, K., Ouyang, P., Shah, R. V., Shay, C. M., & Anderson, C. A. M. (2017). CT-Derived Body Fat Distribution and Incident Cardiovascular Disease: The Multi-Ethnic Study of Atherosclerosis. The Journal of clinical endocrinology and metabolism, 102(11), 4173–4183. https://doi.org/10.1210/jc.2017-01113
Mongraw-Chaffin, M., Allison, M. A., Burke, G. L., Criqui, M. H., Matsushita, K., Ouyang, P., Shah, R. V., Shay, C. M., & Anderson, C. A. M. (2017). CT-Derived Body Fat Distribution and Incident Cardiovascular Disease: The Multi-Ethnic Study of Atherosclerosis. The Journal of clinical endocrinology and metabolism, 102(11), 4173–4183. https://doi.org/10.1210/jc.2017-01113
Nagayama, D., Watanabe, Y., Yamaguchi, T., Maruyama, M., Saiki, A., Shirai, K., & Tatsuno, I. (2020). New index of abdominal obesity, a body shape index, is BMI-independently associated with systemic arterial stiffness in real-world Japanese population. International journal of clinical pharmacology and therapeutics, 58(12), 709–717. https://doi.org/10.5414/CP203778
Sá, D., Mendonça, M. I., Sousa, F., Abreu, G., Ferreira, M., Henriques, E., Freitas, S., Rodrigues, M., Borges, S., Guerra, G., Drumond, A., Sousa, A. C., & Dos Reis, R. P. (2025). Association of Obesity-Related Genetic Variants with Android Fat Patterning and Cardiometabolic Risk in Women. Genes, 16(9), 1019. https://doi.org/10.3390/genes16091019
Sančanin B., Penjišević A. (2024). Reducing obesity risk: prevention strategies and influencing factors. MEDIS – International Journal of Medical Sciences and Research, 3(4), 19-24. https://doi.org/10.35120/medisij030419s
Smith, S., & Madden, A. M. (2016). Body composition and functional assessment of nutritional status in adults: a narrative review of imaging, impedance, strength and functional techniques. Journal of human nutrition and dietetics : the official journal of the British Dietetic Association, 29(6), 714–732. https://doi.org/10.1111/jhn.12372
Sweatt, K., Garvey, W. T., & Martins, C. (2024). Strengths and Limitations of BMI in the Diagnosis of Obesity: What is the Path Forward?. Current obesity reports, 13(3), 584–595. https://doi.org/10.1007/s13679-024-00580-1
Thomas, D. M., Bredlau, C., Bosy‐Westphal, A., Mueller, M., Shen, W., Gallagher, D., ... & Heymsfield, S. B. (2013). Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity, 21(11), 2264-2271.
Toombs, R. J., Ducher, G., Shepherd, J. A., & De Souza, M. J. (2012). The impact of recent technological advances on the trueness and precision of DXA to assess body composition. Obesity (Silver Spring, Md.), 20(1), 30–39. https://doi.org/10.1038/oby.2011.211
WHO, W. (2008). STEPwise approach to surveillance (STEPS). World Health Organization (WHO), Geneva, Switzerland.
World Health Organization. (2011). Waist circumference and waist–hip ratio: Report of a WHO expert consultation, Geneva, 8–11 December 2008. World Health Organization. https://www.who.int/publications/i/item/9789241501491

