Skip to main content
Log in

Prediction of body fat in adolescents: validity of the methods relative fat mass, body adiposity index and body fat index

  • Original Article
  • Published:
Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity Aims and scope Submit manuscript

Abstract

Objective

To verify the validity of anthropometric methods body adiposity index (BAI), relative fat mass (RFM) and body fat index (BFI) to estimate body fat percentage (%BF) in adolescents.

Methods

A cross-sectional study was carried out with 420 Brazilian adolescents aged 15–19 years, stratified by age (< 18 years, n = 356; ≥ 18 years, n = 64) and sex (boys, n = 216; girls, n = 204). The Anthropometric measurements height, body weight, hip circumference and waist circumference were collected to calculate the %BF by BAI, RFM, BFI methods. Subsequently, %BF was measured by dual emission X-ray absorptiometry (DXA), adopted as a reference method. In the statistical analysis of the data, the Pearson correlation test and the paired t test between %BF obtained by the equations and by the DXA were performed. The method validation criterion was that 68% of individuals should be within an acceptable error range of ± 3.5% of BF and Cohen's Kappa index ≥ 0.61. Additionally, the Bland–Altman graphical analysis was performed.

Results

All methods showed a high correlation with DXA. For the Kappa index, only the RFM reached the criterion in the total sample (0.67) and in the sample < 18 years (0.68). None of the methods reached the criterion of 68% of the sample within the error range of ± 3.5% of BF.

Conclusion

The BAI, RFM and BFI equations were not valid for predicting BF in the studied sample according to the criteria adopted regardless of sex or age.

Level of evidence

Level V, cross-sectional descriptive study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

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

Similar content being viewed by others

Data availability

All relevant data are within the manuscript.

References

  1. World Health Organization (2017) Facts and figures on childhood obesity. Last accessed date May 13th, 2021. Available at: http://www.who.int/end-childhood-obesity/facts/en/

  2. Berg AH, Scherer PE (2005) Adipose tissue, inflammation, and cardiovascular disease. Circ Res 96:939–949. https://doi.org/10.1161/01.RES.0000163635.62927.34

    Article  CAS  PubMed  Google Scholar 

  3. Hjartåker A, Langseth H, Weiderpass E (2008) Obesity and diabetes epidemics. Innov. Endocrinol. Cancer, Springer 72–93. https://doi.org/10.1007/978-0-387-78818-0_6

  4. Lauby-Secretan B, Scoccianti C, Loomis D et al (2016) Body Fatness and Cancer-Viewpoint of the IARC Working Group. N Engl J Med 375:794–798. https://doi.org/10.1056/NEJMsr1606602

    Article  PubMed  PubMed Central  Google Scholar 

  5. Zheng Y, Manson JE, Yuan C et al (2017) Associations of weight gain from early to middle adulthood with major health outcomes later in life. JAMA 318:255–269. https://doi.org/10.1001/jama.2017.7092

    Article  PubMed  PubMed Central  Google Scholar 

  6. Reilly JJ, Kelly J (2011) Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review. Int J Obes 35:891–898. https://doi.org/10.1038/ijo.2010.222

    Article  CAS  Google Scholar 

  7. Tomiyama AJ, Hunger JM, Nguyen-Cuu J, Wells C (2016) Misclassification of cardiometabolic health when using body mass index categories in NHANES 2005–2012. Int J Obes 40:883–886. https://doi.org/10.1038/ijo.2016.17

    Article  CAS  Google Scholar 

  8. Martin AD, Drinkwater DT (1991) Variability in the measures of body fat. Assumptions or technique? Sports Med Auckl NZ 11:277–288. https://doi.org/10.2165/00007256-199111050-00001

    Article  CAS  Google Scholar 

  9. Bergman RN, Stefanovski D, Buchanan TA et al (2011) A better index of body adiposity. Obes Silver Spring Md 19:1083–1089. https://doi.org/10.1038/oby.2011.38

    Article  Google Scholar 

  10. Woolcott OO, Bergman RN (2018) Relative fat mass (RFM) as a new estimator of whole-body fat percentage ─ a cross-sectional study in American adult individuals. Sci Rep 8:10980. https://doi.org/10.1038/s41598-018-29362-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yang HI, Cho W, Ahn KY et al (2020) A new anthropometric index to predict percent body fat in young adults. Public Health Nutr 23:1507–1514. https://doi.org/10.1017/S1368980019004191

    Article  PubMed  Google Scholar 

  12. Vlassopoulos A, Combet E (2005) Lean MEJ (2014) Changing distributions of body size and adiposity with age. Int J Obes 38:857–864. https://doi.org/10.1038/ijo.2013.216

    Article  Google Scholar 

  13. Cerqueira MS, Santos CAD, Silva DAS et al (2018) Validity of the Body Adiposity Index in Predicting Body Fat in Adults: a systematic review. Adv Nutr Bethesda Md 9:617–624. https://doi.org/10.1093/advances/nmy043

    Article  Google Scholar 

  14. Wickel EE (2014) Evaluating the utility of the body adiposity index in adolescent boys and girls. J Sci Med Sport 17:434–438. https://doi.org/10.1016/j.jsams.2013.06.002

    Article  PubMed  Google Scholar 

  15. De Santis FM, Cecon RS, de Faria ER et al (2019) Agreement of body adiposity index (BAI) and paediatric body adiposity index (BAIp) in determining body fat in Brazilian children and adolescents. Public Health Nutr 22:132–139. https://doi.org/10.1017/S1368980018002458

    Article  Google Scholar 

  16. de Macêdo CT, de Almeida-Neto PF, de Matos DG et al (2021) Evaluation of the body adiposity index against dual-energy X-ray absorptiometry for assessing body composition in children and adolescents. Am J Hum Biol Off J Hum Biol Counc 33:e23503. https://doi.org/10.1002/ajhb.23503

    Article  Google Scholar 

  17. Woolcott OO, Bergman RN (2019) Relative Fat Mass as an estimator of whole-body fat percentage among children and adolescents: a cross-sectional study using NHANES. Sci Rep 9:15279. https://doi.org/10.1038/s41598-019-51701-z

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. de Onis M, Onyango AW, Borghi E et al (2007) Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ 85:660–667. https://doi.org/10.2471/blt.07.043497

    Article  PubMed  PubMed Central  Google Scholar 

  19. Verhaegen AA, Van Gaal LF (2021) Drugs Affecting Body Weight, Body Fat Distribution, and Metabolic Function-Mechanisms and Possible Therapeutic or Preventive Measures: an Update. Curr Obes Rep 10:1–13. https://doi.org/10.1007/s13679-020-00419-5

    Article  PubMed  Google Scholar 

  20. Marfell-Jones MJ, Stewart AD, De Ridder JH (2012) International standards for anthropometric assessment. http://hdl.handle.net/11072/1510

  21. Bazzocchi A, Ponti F, Albisinni U et al (2016) DXA: technical aspects and application. Eur J Radiol 85:1481–1492. https://doi.org/10.1016/j.ejrad.2016.04.004

    Article  PubMed  Google Scholar 

  22. George D, Mallery P (2019) IBM SPSS statistics 26 step by step: A simple guide and reference. Routledge

  23. Watson PF, Petrie A (2010) Method agreement analysis: a review of correct methodology. Theriogenology 73:1167–1179. https://doi.org/10.1016/j.theriogenology.2010.01.003

    Article  CAS  PubMed  Google Scholar 

  24. Cohen J (1960) A Coefficient of Agreement for Nominal Scales. Educ Psychol Measur 20:37–46. https://doi.org/10.1177/001316446002000104

    Article  Google Scholar 

  25. Lohman TG (1987) The use of skinfold to estimate body fatness on children and youth. J Phys Educ Recreat Dance 58:98–103. https://doi.org/10.1080/07303084.1987.10604383

    Article  Google Scholar 

  26. Bottaro MF, Heyward VH, Bezerra RF, Wagner DR (2002) Skinfold method vs dual-energy x-ray absorptiometry to assess body composition in normal and obese women. J Exerc Physiol Online 5:11–18

    Google Scholar 

  27. Doran DA, Mc Geever S, Collins KD et al (2014) The validity of commonly used adipose tissue body composition equations relative to dual energy X-ray absorptiometry (DXA) in gaelic games players. Int J Sports Med 35:95–100. https://doi.org/10.1055/s-0033-1333693

    Article  CAS  PubMed  Google Scholar 

  28. Krouwer JS (2008) Why Bland-Altman plots should use X, not (Y+X)/2 when X is a reference method. Stat Med 27:778–780. https://doi.org/10.1002/sim.3086

    Article  PubMed  Google Scholar 

  29. Ripka WL, Orsso CE, Haqq AM et al (2020) Validity and accuracy of body fat prediction equations using anthropometrics measurements in adolescents. Eat Weight Disord EWD 26:879–886. https://doi.org/10.1007/s40519-020-00918-3

    Article  PubMed  Google Scholar 

  30. Flegal KM, Graubard B (2005) Ioannidis JPA (2020) Use and reporting of Bland-Altman analyses in studies of self-reported versus measured weight and height. Int J Obes 44:1311–1318. https://doi.org/10.1038/s41366-019-0499-5

    Article  Google Scholar 

  31. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet Lond Engl 1:307–310. https://doi.org/10.1016/S0140-6736(86)90837-8

    Article  CAS  Google Scholar 

  32. Johnson W, Chumlea WC, Czerwinski SA, Demerath EW (2012) Concordance of the recently published body adiposity index with measured body fat percent in European-American adults. Obes Silver Spring Md 20:900–903. https://doi.org/10.1038/oby.2011.346

    Article  Google Scholar 

  33. Segheto W, Coelho FA, Guimarães C, da Silva D et al (2017) Validity of body adiposity index in predicting body fat in Brazilians adults. Am J Hum Biol Off J Hum Biol Counc. https://doi.org/10.1002/ajhb.22901

    Article  Google Scholar 

  34. Jager J, Putnick DL, Bornstein MH (2017) II. More than just convenient: the scientific merits of homogeneous convenience samples. Monogr Soc Res Child Dev 82:13–30. https://doi.org/10.1111/mono.12296

    Article  PubMed  PubMed Central  Google Scholar 

  35. Silva AM, Fields DA, Sardinha LB (2013) A PRISMA-driven systematic review of predictive equations for assessing fat and fat-free mass in healthy children and adolescents using multicomponent molecular models as the reference method. J Obes 2013:148696. https://doi.org/10.1155/2013/148696

    Article  PubMed  PubMed Central  Google Scholar 

  36. Messina C, Albano D, Gitto S, et al (2020) Body composition with dual energy X-ray absorptiometry: from basics to new tools. Quant Imaging Med Surg 10:1687–1698. https://doi.org/10.21037/qims.2020.03.02

Download references

Acknowledgements

The equipment for data collection in the present study was provided by the Human Performance Laboratory of the Department of Physical Education, Federal University of Viçosa, headed by Professor João Carlos Bouzas Marins.

Funding

No funds, grants, or other support was received.

Author information

Authors and Affiliations

Authors

Contributions

IGAE and MSC contributed to all parts of this study. JCBM, PM and DS are responsible for data interpretation and manuscript revision. All authors approved the final manuscript.

Corresponding author

Correspondence to Irismar G. A. Encarnação.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest.

Ethical approval

The study protocol has been approved by the ethics committee of the Universidade Federal de Viçosa (Plataforma Brasil system, nº CAAE 99311418.0.0000.5153).

Informed consent

All of the participants signed and approved a written informed consent before participation in the study.

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

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Encarnação, I.G.A., Cerqueira, M.S., Silva, D.A.S. et al. Prediction of body fat in adolescents: validity of the methods relative fat mass, body adiposity index and body fat index. Eat Weight Disord 27, 1651–1659 (2022). https://doi.org/10.1007/s40519-021-01301-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40519-021-01301-6

Keywords

Navigation