Development and Validation of a Skin Fold Thickness Prediction Equation for Asian Indians Using Hydrodensitometry

Abstract

There is increasing evidence that the associations between body mass index (BMI), body fat percentage (body fat %) and body fat distribution differ across populations [1]. Particularly in the Asian population, a specific BMI reflects a higher percentage of body fat than in white or European populations [1]. Obesity is defined as an excessive amount of adipose tissue with body fat % ≥ 25% in males, ≥32% in females [2]. BMI which is essentially weight (kg)/ height 2 (m 2 ), is a measure of relative weight and is an acceptable proxy for thinness and fatness and has been directly related to health risks and death rates in many populations [1]. Thus BMI is often used as a surrogate measure of obesity, because of the difficulties in accurately estimating body fat %, though BMI fails to distinguish between body fat and lean mass. Considering the relation of BMI cut offs with health risks, the cut off values for obesity using BMI were established as BMI Method: 137 healthy people (77 males and 60 females), in the age group of 30-60 years were included in the study. With hydrodensitometry, anthropometric measurements such as height, weight, 10 skin folds thickness sites, 5 sites of circumference, 5 sites of bone breadths and DEXA scans were taken as variables. A linear regression model was then created for both males and females, with body fat % calculated by hydrodensitometry used as a dependent variable and other anthropometric measurements and DEXA results used as independent variables.Results: 4 new body fat estimation models, 2 for males and 2 for females were obtained for Asian Indians with R2 of 0.90 and 0.71 for males and 0.90 and 0.72 for females respectively. Conclusion: The new prediction equations for body fat % estimation, which were derived and internally validated in an adult Indian population revealing a lower error difference than previously developed models.