
Estimation of percentage of body fat in field studies – a method based on relative elbow breadth (Frame Index) and BMI
Author(s) -
Rebekka Mumm,
Anna Reimann,
Christiane Scheffler
Publication year - 2021
Publication title -
human biology and public health
Language(s) - English
Resource type - Journals
ISSN - 2748-9957
DOI - 10.52905/hbph.v1.3
Subject(s) - overweight , body mass index , medicine , obesity , estimator , demography , estimation , index (typography) , statistics , mathematics , computer science , management , sociology , world wide web , economics
Background
Over the last 20 years, a decreasing trend in external skeletal robusticity and an increasing trend in overweight and obesity was observed worldwide in adults and children as modern lifestyles in nutritional and activity behavior have changed. However, body mass index (BMI) as a measure for overweight is not an ideal predictor of % body fat (%BF) either in children and adolescents or in adults. On the contrary, it disguises a phenomenon called “hidden obesity”.
Objectives
We aim to approximate %BF by combining skeletal robusticity and BMI and develop an estimation-based tool to identify normal weight obese children and adolescents.
Sample and Methods
We analyzed cross-sectional data on height, weight, elbow breadth, and skinfold thickness (triceps and subscapular) of German children aged 6 to 18 years (N=15,034). We used modified Hattori charts and multiple linear regression to develop a tool, the “%BF estimator”, to estimate %BF by using BMI and skeletal robusticity measured as Frame Index.
Results
Independent of sex and age an increase in BMI is associated with an increase in %BF, an increase in Frame Index is associated with a decrease in %BF. The developed tool “%BF estimator” allows the estimation of %BF per sex and age group after calculation of BMI and Frame Index.
Conclusion
The “%BF estimator” is an easily applicable tool for the estimation of %BF in respect of body composition for clinical practice, screening, and public health research. It is non-invasive and has high accuracy. Further, it allows the identification of normal weight obese children and adolescents.