Comparison of anthropometric equations to estimate body fat | 76126


Comparison of anthropometric equations to estimate body fat in subjects with overweight

Author(s): Martins, Guilherme Quaiato1; Matheus, Silvana Corrêa2; Santos, Daniela Lopes Dos2; Both, Diego Rodrigo3; Farinha, Juliano Boufleur3; Martins, Mariane da Silveira4

Introduction: Obesity has been the subject of several studies that highlight its prevalence, as well as risk factors. Due to the excessive accumulation of body fat lead to health problems of the people, it is important to check the amount and distribution of body fat by assessing body composition. Some prediction equations of body fat percentage (%BF) have been developed for the purpose of having the willingness practical means for the determination of %BF.

Objective: To compare the equations proposed by Deurenberg et al. Lean et al. and Gomez Ambrosi et al. to determine the body fat of overweight and obese subjects, with the reference method by dual-energy x-ray absorptiometry (DXA).

Methods: We conducted 78 assessments with individuals of both sexes overweight and obese aged between 35 and 68 years. The % BF was obtained by DXA (reference method) and the equations of Deurenberg et al., Lean et al. and Gomez-Ambrosi et al. called CUNBAE (Clínica Universidad de Navarra-Body Adiposity Estimator). We used the Kolgomorov-Smirnov test for data abnormality and the accuracy of the results the paired t test, Pearson correlation, Bland & Altman analysis.

Results: The equations showed no statistically significant difference from the reference value (DXA). There was high correlational (r = 0,86 to 0,91) between the % BF of equations and the reference method, and average results of the difference -0,4% to 0,1%, but with high dispersion values (range 8,4% to -7,8%).

Conclusion: Although the equations used in this study have presented high dispersion values in the analysis of compliance with the reference method, the use of these may have considerable importance in estimating the body fat of large population groups.

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Journal Highlights
  • Blood Glucose
  • Dietary Supplements
  • Cholesterol, Dehydration
  • Digestion
  • Electrolytes
  • Clinical Nutrition Studies
  • energy balance
  • Diet quality
  • Clinical Nutrition and Hospital Dietetics