As a measure of health, the percentage of body fat has been utilized for many ergonomist, physician, athletic trainers, and work physiologists. Underwater weighing procedure for measuring the percentage of body fat is popular and accurate. However, it is relatively expensive, difficult to perform and requires large space. Anthropometric techniques can be utilized to predict the percentage of body fat in the field setting because they are easy to implement and require little space. In this concern, the purpose of this study was to find a regression model to easily predict the percentage of body fat using the anthropometric circumference measurements as predictor variables. In this study, the data for 10 anthropometric circumference measurements for 252 men were analyzed. A full model with ten predictor variables was constructed based on subjective knowledge and literature. The linear regression modeling consists of variable selection and various assumptions regarding the anticipated model. All possible regression models and the assumptions are evaluated using various statistical methods. Based on the evaluation, a reduced model was selected with five predictor variables to predict the percentage of body fat. The model is : % Body Fat = 2.704-0.601 (Neck Circumference) + 0.974 (Abdominal Circumference) -0.332 (Hip Circumference) + 0.409 (Arm Circumference) - 1.618 (Wrist Circumference) + ε. This model can be used to estimate the percentage of body fat using only a tape measure.

The purpose of this study was to compare the validity of obesity indices among the body mass index (BMI), waist circumference (WC), and body fat percentage (BF%), and to determine which is the most useful index to predict the risk of chronic diseases of elderly people. This study was conducted as a cross-sectional study at welfare centers in Seoul. The total number of subjects was 261 (68 men and 193 women) with age ≥60 years. The distribution of obesity using 3 obesity indices in the subjects with hypertension, diabetes, or arthritis was BF%>WC>BMI in elderly men and WC>BF%>BMI in elderly women. In elderly women, odds ratios (ORs) for hypertension in BMI and WC quartiles were significantly increased in quartile 2 and 3 (p<0.05). The ORs for hypertension, hyperlipidemia, and arthritis in BF% quartiles were significantly increased in quartile 3 and 4 (p<0.05). The BF% was sensitive obesity index for predicting the occurrence of chronic disease in men, and the WC was sensitive index in women. Our results suggested maintaining BMI less than 23.5 kg/m2, WC less than 82 cm, and BF less than 35% in order to prevent chronic diseases in elderly women.