Skip to main content

Does FMI Correlate Better than BMI with the Occurrence of Metabolic Changes in Obese Patients? Study Based on 2007 Consecutive Mexican Patients

Obesity Surgery volume 30, pages 1324–1331 (2020)Cite this article

Abstract

Background

The body mass index (BMI) is the most commonly used anthropometric indicator. However, it does not discern among the different body components. The body fat content, expressed as fat mass index (FMI), is an accurate way to estimate adiposity. Since most metabolic diseases are associated with excess fat tissue, our aims were to comparatively analyze the frequency of associated metabolic abnormalities in patients with different obesity degrees based on BMI and FMI and to determine the best cut-off value of both indicators to predict metabolic abnormalities.

Methods

From a cohort of 2007 patients, BMI and FMI were calculated using DXA. Individuals were classified into the different obesity degrees according to the reference ranges from the World Health Organization (WHO) and the National Health and Nutrition Examination Survey (NHANES). A comparative analysis between BMI, FMI, and their correlation to the presence of metabolic alterations was performed.

Results

BMI underestimated the degree of obesity when compared with FMI. Spearman’s rank-order correlation for both indexes resulted in very high coefficients (rho Spearman’s = 0.857; p = 0.0001). The prevalence of metabolic alterations increased as BMI and FMI also increased. Despite the high positive statistical correlation between BMI and FMI, it was seen that some comorbidities were more specifically related to one particular index.

Conclusions

There were no significant differences between the BMI and the FMI for predicting the degree of obesity. Likewise, there were no significant differences between them for the prediction of metabolic alterations.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

References

  1. Ranasinghe C, Gamage P, Katulanda P, et al. Relationship between body mass index and body fat percentage, estimated by bioelectrical impedance, in a group of Sri Lankan adults: a cross sectional study. BMC Public Health. 2013;13:1–8.

    Article  Google Scholar 

  2. Hernández CP, Flores CA, Rocha MAD, et al. Composición corporal en mujeres derechohabientes del IMSS que acuden al Servicio de Densitometría. El Residente. 2012;7:6–15.

    Google Scholar 

  3. Lorente RRM, Azpeitia AJ, Arévalo GN, et al. Absorciometría con rayos X de doble energía. Fundamentos, metodología y aplicaciones clínicas, vol. 54: Elsevier; 2012. p. 410–23.

  4. Charon GR, Berger M, Garg RK, et al. Measures of adiposity and cardiovascular disease risk factors, New York City Health and Nutrition Examination Survey, 2004. Prev Chronic Dis. 2011;8:1–10.

    Google Scholar 

  5. Schuster J, Vogel P, Eckhardt C, et al. Applicability of the visceral adiposity index (VAI) in predicting components of metabolic syndrome in young adults. Nutr Hosp. 2014;30:806–12.

    PubMed  Google Scholar 

  6. Albanese CV, Diessel E, Genant HK. Clinical applications of body composition measurements using DXA. J Clin Densitom. 2003;6:75–85.

    Article  Google Scholar 

  7. Kelly TL, Wilson KE, Heymsfield SB. Dual energy X-Ray absorptiometry body composition reference values from NHANES. PLoS ONE. 2009;4:1–8.

    Article  Google Scholar 

  8. American Diabetes Association (ADA). Standard Medical Care in Diabetes 2018. J Clin Appl Res Educ. 2018;41:1–150.

    Google Scholar 

  9. Cifu AS, Davis AM. Prevention, detection, evaluation, and management of high blood pressure in adults. JAMA. 2017;318:2132–4.

    Article  Google Scholar 

  10. Jellinger PS, Handelsman Y, Rosenblit PD, et al. (2017). AACE AND ACE guidelines for management of dyslipidemia and prevention of cardiovascular disease. Endocr Pract. 2017;23:479–97.

    Article  Google Scholar 

  11. Roubenoff R, Dallal GE, Wilson PWF. Predicting body fatness: the body mass index vs estimation by bioelectrical impedance. Am J Public Health. 1995;85:726–8.

    CAS  Article  Google Scholar 

  12. Fatima SS, Rehman R, Chaudhry B. Body mass index or body fat! Which is a better obesity scale for Pakistani population? J Pak Med Assoc. 2014;64:1225–8.

    PubMed  Google Scholar 

  13. Fernández-Real JM, Vayreda M, Casamitjana R, et al. Body mass index (MBI) and percent fat mass. A BMI > 27.5 Kg/m2 could be indicative of obesity in the Spanish population. Med Clin. 2001;117:681–4.

    Article  Google Scholar 

  14. Razak F, Anand SS, Shannon H, et al. Defining obesity cut points in a multiethnic population. Circulation. 2007;115:2111–8.

    Article  Google Scholar 

  15. Ärnlöv J, Sundström J, Ingelsson E, et al. Impact of BMI and the metabolic syndrome on the risk of diabetes in middle-aged men. Diabetes Care. 2011;34:61–5.

    Article  Google Scholar 

  16. MacMahon S, Baigent C, Duffy S, et al. Body mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet. 2009;373:1083–96.

    Article  Google Scholar 

  17. Deurenberg P, Yap M, Van Staveren WA. Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes. 1998;22:1164–71.

    CAS  Article  Google Scholar 

  18. Schutz Y, Kyle UUG, Pichard C. Fat-free mass index and fat mass index percentiles in caucasians aged 18-98 y. Int J Obes. 2002;26:953–60.

    CAS  Article  Google Scholar 

  19. Deurenberg-Yap M, Schmidt G, van Staveren WA, et al. The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore. Int J Obes Relat Metab Disord. 2000;24:1011–7.

    CAS  Article  Google Scholar 

  20. De Schutter A, Lavie CJ, Arce K, et al. Correlation and discrepancies between obesity by body mass index and body fat in patients with coronary heart disease. J Cardiopulm Rehabil Prev. 2013;33:77–83.

    Article  Google Scholar 

  21. Lu Y, Shu H, Zheng Y, et al. Comparison of fat-free mass index and fat mass index in Chinese adults. Eur J Clin Nutr. 2012;66:1004–7.

    CAS  Article  Google Scholar 

  22. Provencher MT, Chahla J, Sanchez G, et al. Body mass index versus body fat percentage in prospective national football league athletes: overestimation of obesity rate in athletes at the national football league scouting combine. J Strength Cond Res. 2018;32:1013–9.

    Article  Google Scholar 

  23. Wildman RP. The obese without cardiometabolic risk factor clustering and the normal weight with cardiometabolic risk factor clustering. Arch Intern Med. 2008;168:1617.

    Article  Google Scholar 

  24. Flowers E, Molina C, Mathur A, et al. Adiposity and cardiovascular risk clustering in South Asians. Metab Syndr Relat Disord. 2013;11:434–40.

    CAS  Article  Google Scholar 

  25. Arnlov J, Ingelsson E, Sundstrom J, et al. Impact of body mass index and the metabolic syndrome on the risk of cardiovascular disease and death in middle-aged men. Circulation. 2010;121:230–6.

    Article  Google Scholar 

  26. Silva-Zolezzi I et al. Analysis of genomic diversity in Mexican Mestizo populations to develop genomic medicine in Mexico. Proc Natl Acad Sci U S A. 2009;106:8611–6.

    CAS  Article  Google Scholar 

Download references

Author information

Affiliations

  1. Center for Nutrition and Obesity, The American British Cowdray Medical Center, Mexico City, Mexico

    Carlos A. Gutiérrez-Rojas, Ruth Cruz-Soto, Verónica Sánchez-Muñoz, Anayeli Romero, Maureen Mosti-Molina, Hugo A. Sánchez-Aguilar & Miguel F. Herrera

  2. Department of Surgery, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico

    David Velázquez-Fernández & Miguel F. Herrera

Authors
  1. Carlos A. Gutiérrez-Rojas
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ruth Cruz-Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Verónica Sánchez-Muñoz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Anayeli Romero
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Maureen Mosti-Molina
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hugo A. Sánchez-Aguilar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. David Velázquez-Fernández
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Miguel F. Herrera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miguel F. Herrera.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

The study does not include animal or human experiments and all personal information was codified to maintain confidentiality.

Consent Statements

Non-applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Gutiérrez-Rojas, C.A., Cruz-Soto, R., Sánchez-Muñoz, V. et al. Does FMI Correlate Better than BMI with the Occurrence of Metabolic Changes in Obese Patients? Study Based on 2007 Consecutive Mexican Patients. OBES SURG 30, 1324–1331 (2020). https://doi.org/10.1007/s11695-019-04289-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11695-019-04289-2

Keywords

  • Obesity
  • Fatty mass index
  • Body mass index
  • DXA
  • Body composition