In this article, we introduce a new method to estimate adiposity of individuals. The “BAI” is a direct estimate of %body fat. The applicability of the BAI to two ethnic groups, Mexican American and African American, is demonstrated. Unlike the BMI, the BAI provides %body fat in both males and females without statistical correction. Calculating BAI does not require a measurement of body weight.
In the present study, we were able to access the BetaGene study of relatives of Mexican-American individuals with gestational diabetes. While this population has an elevated risk for type 2 diabetes overall, the range of fat deposition in this population, ranging from 8.7 to 61.2% made it particularly attractive to examine a new measure of body fat. Because DXA-measured %fat was available to us, we considered this to be the “gold standard” that would indicate to a physician the adiposity of the patient. We then asked how to best estimate the %fat from easily accessible variables. In this population, %fat was positively correlated with hip circumference, and negatively correlated with height. Surprisingly, there was a weaker correlation with body weight. Therefore, we defined a body fat index in terms of a nonlinear ratio of hip circumference to height. The selected relationship, hip size divided by height to the power of 1.5, yielded the strongest correlation with DXA-derived %fat estimates. In fact, we observed a quasi-linear relationship between the BAI and %body fat, and suggested it as a preliminary adiposity index.
Observing all the BetaGene subjects, two interesting points emerged. One was that the relationship between BAI and %adiposity was not different between men and women. Thus, if one proposes cutoffs of risk in terms of adiposity, one does not have to propose separate parameters for the two sexes. The second and purely fortuitous point was that the slope of the relationships between the BAI and %adiposity had a slope close to 1.0. Because the intercept of the relationship between adiposity and the preliminary index had a negative intercept, we were able to define the final adiposity index, the BAI as
Of course, it may not be trivial for all individuals to calculate the value of BAI, but the computation can be made easily with a calculator or a computer program (c.f., for example: ba-index.org).
There are, of course other procedures that could be used to define a simple-to-use estimate of adiposity. One approach which is often used is the multiple regression approach. Using this approach one assumes a linear relationship between the primary outcome variable (in this case, %body adiposity) and known determining variables. For example, it is possible to calculate this relationship for the BetaGene data:
(in this expression, sex term is 1 for males and 0 for females.)
An important question is whether such a complex equation would be useful for the practicing clinician. A different set of parameters could be calculated for different ethnic groups. We suggest that it is extremely unlikely that a multiple regression approach will be accepted and used clinically. The strongest evidence is that, regardless of its known faults, the BMI is still in wide use because of its simplicity; it has not yet been supplanted by a more cumbersome (if accurate) approach. In fact, PubMed reveals over 45,000 references using the BMI as of this writing.
In this study, the BAI was developed and validated from studies of non-Caucasian subjects, and thus the utility of this index has not yet been confirmed in Caucasian subjects. Many population studies have focused on white populations (Framingham (22
), Inter99 (23
), Botnia (24
), FUSION (17
)). Thus, it might be expected that our index would be developed in whites. However, most of the world population is nonwhite. Thus, it is equally reasonable to develop an index in a “non-Caucasian” population. We have used the Mexican-American population, which is prevalent in Los Angeles. It is possible that our results could be extrapolated to several populations in Central and South America. We also compared the behavior of the BAI in an African-American population in the Washington, D.C. area, and found that the behavior of the index in Mexican-Americans and African-Americans is quite similar ( and ). In addition, there is some evidence in our paper that the BAI is useful in whites, but the latter requires further investigation. Thus, we believe that we have presented evidence of accuracy at least in two ethnic populations, and further research on the generalizability of BAI to other groups is underway.
Bland and Altman’s limits-of-agreement plot between %body adiposity and BAI-18 for the TARA cohort. BAI, body adiposity index; DXA, dual-energy X-ray absorptiometry.
One underlying assumption in this work is that %adiposity per se
is the physiological characteristic of obese and overweight individuals, which puts such individuals at-risk for cardiovascular disease. The relationship between %fat and risk for cardiovascular disease is well documented (25
). However, there is compelling evidence that visceral (27
) or hepatic (28
) fat content may be a stronger predictor of cardiovascular risk than overall adiposity. Hip size in this study must reflect both visceral as well as subcutaneous (thigh) adiposity, as it reflects overall %fat in men and women. We do not have individual measurements of visceral and subcutaneous fat deposition for the BetaGene study, so it is not possible at this time to determine whether the BAI might reflect the presumably more detrimental visceral or hepatic compartments, but it will be of interest in the future to compare the BAI to selected fat depots.
It was important to validate the BAI in a separate ethnic group. We were able to access the TARA study, for which %fat, hip size, and height had been assessed. It was interesting that in the TARA study of African-American participants, the ability of the BAI to predict %fat was very similar to the Mexican-American participants of the BetaGene study. While comparing two ethnic groups is encouraging, it remains unknown at this time if the BAI will have this predictive property of %adiposity in other ethnic groups. Of course, a Caucasian population should be studied, as well as other ethnic groups such as Chinese, Koreans, Japanese, and those from the Indian subcontinent. Because of the increasing importance of childhood obesity, it is critical to examine the behavior of the BAI in pre-pubertal and postpubertal children of both sexes, and different ethnicities. Questions to be addressed include whether the BAI can predict %adiposity in children, and the extent to which such prediction can be associated with risk of disease such as diabetes and cardiovascular disease.
One of the surprising results in this analysis was that %adiposity could be well estimated without using a mechanical or electronic assessment of body weight. Thus, even in remote environments where only the simplest and least expensive tools are available (a tape measure), a reliable estimate of adiposity may be obtained. While the height of mature individuals is relatively constant, it is the measurement of hip circumference that potentially may introduce error to the estimation of BAI. Considering the fact that hip circumference is the numerator of the fraction defining BAI, a 10% change in hip circumference will result in a similar error in the estimation of BAI. Nevertheless, a 10% difference for an average value of BAI of 33 will result in error in the estimation of ±3 in the value of BAI, which likely has little significance relative to risk. This provides hope for providing important information to practitioners and patients in a very wide variety of environments. It will be important to examine the application of this method in widely diverse populations.
In summary, we have defined a new parameter of adiposity. We used the DXA measured %body fat as our “gold standard,” and asked which easily measured anthropomorphic parameters could be combined to obtain an easy measure related to %adiposity. Because of the particularly strong correlation of both hip size and height, the resultant parameter, the BAI, is a strong predictor of %fat in Mexican-American subjects of widely varying adiposity. The result was confirmed in a study of African-Americans. After further validation, this measure can be proposed as a useful measure of %fat, which is very easy to obtain. However, it remains to be seen if the BAI is a more useful predictor of health outcome, in both males and females, than other indexes of body adiposity, including the BMI itself.