ISPUB.COM The Internet Journal of Health Volume 12 Number 1 1 of 7 Development of the Health Index (HI) Statistical Equation as an Alternative Clinical Parameter to the Body Mass Index in the Prediction of Body Fat Percentage M Hernandez, P Shah, P Hardigan, C Blavo, R Tofts, D Sider, V Pai, A Lawrence, I Ally, J Dergham, A Gratzon, E McDaniel, A Boyrazian, J Bennett, S Thames, K McCurdy, J McConnell, U Khalid, S Chowdhury, H Brar, O Raj, R Talwar Citation M Hernandez, P Shah, P Hardigan, C Blavo, R Tofts, D Sider, V Pai, A Lawrence, I Ally, J Dergham, A Gratzon, E McDaniel, A Boyrazian, J Bennett, S Thames, K McCurdy, J McConnell, U Khalid, S Chowdhury, H Brar, O Raj, R Talwar. Development of the Health Index (HI) Statistical Equation as an Alternative Clinical Parameter to the Body Mass Index in the Prediction of Body Fat Percentage. The Internet Journal of Health. 2009 Volume 12 Number 1. Abstract Metabolic syndrome is increasing in prevalence in the United States. Body Mass Index is a formula most commonly used to assess body fat percentage. However, the formula contains significant limitations and inefficiencies. As a result, the Health Index equation was developed as an alternative to the BMI. Data from 79 healthy individuals, as defined by the absence of metabolic syndrome risk factors, was collected and a relationship was established between their BMI and body fat percentage. The results showed the BMI produced a poor correlation with the body fat percentage while the Health Index metric produced a stronger correlation to actual body fat percentage. INTRODUCTION Metabolic syndrome, a combination of risk factors which increases the risk for cardiovascular disease, diabetes, which all-cause mortality, affects as much as one quarter of the United States population. ¬1-5 The prevalence of metabolic syndrome is increasing in the United States 6 and the cause may be visceral fat mediated insulin resistance, through various cytokines. 7 Central obesity is perhaps the most important risk factor. 8-13 However, other risk factors, such as stress 14-15 , sedentary lifestyle 8 , aging 8 , lipodystrophy 8 , and rheumatic diseases have also been proposed. 16 In most cases of metabolic syndrome, the Body Mass Index (BMI), a statistical measure used to estimate healthy body weight based on a person’s height, is the tool used to distinguish between underweight, overweight, and obese patients. 19-22 However, it has significant limitations. First of all, BMI is stature dependent. Therefore, individuals with shorter legs have higher BMIs. 23 Further, the BMI differs between cultures. For instance, in Japan, the BMI’s upper limit of normal is 8% which is lower than standards used in the United States. 24-25 Perhaps most importantly, the BMI cannot distinguish between mass due to muscle and mass due to fat, thus making it “as much a measure of lean body mass as it is a measure of fatness or obesity.” 23 Therefore, when a patient loses muscle (and gains proportionately in fat) it actually decreases (because muscle is denser than fat) and when a patient gains muscle and loses fat, it increases (for the same reason). As a result, BMI is an inconsistent predictor of physical health and obesity-related health risk. Other measures, such as waist-circumference are much better predictors. 26-32 In fact, studies have shown that even at low BMIs, high body fat percentage is an important predictor of cardiovascular risk. 33 Since visceral fat is an important etiologic cause of metabolic syndrome complications, the BMI must be adjusted or replaced by an equation which is based on body fat percentage, since this may lead to better prediction of clinical end points (such as diabetes, coronary heart disease, and stroke). 34-38