scispace - formally typeset
Open AccessJournal ArticleDOI

A Better Index of Body Adiposity

Reads0
Chats0
TLDR
A new parameter, the body adiposity index (BAI), which can be calculated from hip circumference and height only, can be used in the clinical setting even in remote locations with very limited access to reliable scales and estimates %adiposity directly.
Abstract
Obesity is a growing problem in the United States and throughout the world. It is a risk factor for many chronic diseases. The BMI has been used to assess body fat for almost 200 years. BMI is known to be of limited accuracy, and is different for males and females with similar %body adiposity. Here, we define an alternative parameter, the body adiposity index (BAI = ((hip circumference)/((height)1.5) − 18)). The BAI can be used to reflect %body fat for adult men and women of differing ethnicities without numerical correction. We used a population study, the “BetaGene” study, to develop the new index of body adiposity. %Body fat, as measured by the dual-energy X-ray absorptiometry (DXA), was used as a “gold standard” for validation. Hip circumference (R = 0.602) and height (R = −0.524) are strongly correlated with %body fat and therefore chosen as principal anthropometric measures on which we base BAI. The BAI measure was validated in the “Triglyceride and Cardiovascular Risk in African-Americans (TARA)” study of African Americans. Correlation between DXA-derived %adiposity and the BAI was R = 0.85 for TARA with a concordance of C_b = 0.95. BAI can be measured without weighing, which may render it useful in settings where measuring accurate body weight is problematic. In summary, we have defined a new parameter, the BAI, which can be calculated from hip circumference and height only. It can be used in the clinical setting even in remote locations with very limited access to reliable scales. The BAI estimates %adiposity directly.

read more

Content maybe subject to copyright    Report

Citations
More filters
Posted ContentDOI

Machine Learning-based Obesity Classification using 3D Body Scanner

TL;DR: In this paper , a machine learning-based obesity classification framework using 3D body scan data, validated it through Accuracy, Recall, Precision, and F1 score, and compared it with BMI and BIA.
Journal ArticleDOI

Waist–hip ratio measured by bioelectrical impedance analysis as a valuable predictor of chronic kidney disease development

TL;DR: In this paper , the risk of chronic kidney disease (CKD) in a middle-aged population was evaluated in association with various body composition metrics, such as waist-hip ratio (WHR), body mass index (BMI), and total body fat.
Journal ArticleDOI

Is there a higher cardiovascular disease risk in Japanese-Brazilians?

TL;DR: The authors intended to evaluate the prevalence of risk factors for cardiovascular disease (CVD) in Japanese-Brazilian subjects and found the study very valuable because it discusses an important public health issue and builds awareness.
References
More filters
Journal ArticleDOI

Statistical methods for assessing agreement between two methods of clinical measurement.

TL;DR: An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
Journal ArticleDOI

Prevalence and trends in obesity among US adults, 1999-2008.

TL;DR: The increases in the prevalence of obesity previously observed do not appear to be continuing at the same rate over the past 10 years, particularly for women and possibly for men.
Journal ArticleDOI

A concordance correlation coefficient to evaluate reproducibility.

TL;DR: A new reproducibility index is developed and studied that is simple to use and possesses desirable properties and the statistical properties of this estimate can be satisfactorily evaluated using an inverse hyperbolic tangent transformation.
Journal ArticleDOI

Indices of relative weight and obesity

TL;DR: The body mass index seems preferable over other indices of relative weight on these grounds as well as on the simplicity of the calculation and, in contrast to percentage of average weight, the applicability to all populations at all times.
Related Papers (5)