Correlation of Air Displacement Plethysmography with Alternative Body Fat Measurement Techniques in Men and Women

International Journal of Exercise Science 5(4) : 367-378, 2012. Obesity has reached epidemic proportions with serious health consequences. Techniques used to measure body fat (BF) yield variable BF estimates, and this variability may lead to underestimation or overestimation of BF and subsequent treatment options. The measurements that are most accurate (Dual-Energy X-ray Absorptiometry (DEXA) and Air Displacement Plethysmography (ADP)) are expensive and often unavailable. The purpose of this study is to find the commonly available BF measurement that is the most accurate and practical for individual body types in the general population and compare these measurements to ADP (BOD POD®) as the standard. Field measurements include skinfolds (SKF), upper, lower, and whole body bioelectrical impedance (BI), waist and hip circumference ratios, body mass index calculations (BMI), and ADP. Our data indicate that BI is the least accurate measurement of body fat in males and females (paired t-tests of % body fat: BI vs. ADP, p0.05). However, preliminary data suggest female- specific SKF equations more accurately predict body fat in obese males than male-specific SKF equations. Given the current obesity trends, it is imperative to update these formulae to accurately reflect the current population

Correlation of Air Displacement Plethysmography with Alternative Body Fat Measurement Techniques in Men and Women

Obesity has reached epidemic proportions with serious health consequences. Techniques used to measure body fat (BF) yield variable BF estimates, and this variability may lead to underestimation or overestimation of BF and subsequent treatment options. The measurements that are most accurate (Dual-Energy X-ray Absorptiometry (DEXA) and Air Displacement Plethysmography (ADP)) are expensive and often unavailable. The purpose of this study is to find the commonly available BF measurement that is the most accurate and practical for individual body types in the general population and compare these measurements to ADP (BOD POD®) as the standard. Field measurements include skinfolds (SKF), upper, lower, and whole body bioelectrical impedance (BI), waist and hip circumference ratios, body mass index calculations (BMI), and ADP. Our data indicate that BI is the least accurate measurement of body fat in males and females (paired t-tests of % body fat: BI vs. ADP, p0.05). However, preliminary data suggest female- specific SKF equations more accurately predict body fat in obese males than male-specific SKF equations. Given the current obesity trends, it is imperative to update these formulae to accurately reflect the current population

Body Composition Predictions From Bioelectric Impedance

The prediction of body composition variables from bioelectric impedance (BI) has considerable potential for use in surveys, because BI is reliable, and the equipment is portable (weight, 1.04 kg). The purpose of the present study was to determine if BI with selected anthropometric variables predicted %BF (percent body fat) accurately. Two groups of sub\u27 jects were used from whom accurate anthropometric variables were ob­tained. The validation group of 148 healthy White adults (77 men; 71 women) aged 18 to 30 was used to formulate two parsimonious models for each sex to predict %BF from selected anthropometric variables, one with­out and one with stature2 divided by resistance (S2/R). The cross-validation group, aged 18 to 30 years (19 White men; 29 White women), was used to assess the stability of equations derived from S2/R and anthropometric vari­ables. Principal component analysis applied to 16 potential predictors showed five components explained most of the variation in %BF. All possi­ble subsets regression procedure was employed to select the best equation on the basis of: (1) five predictors at most, (2) minimum root mean square error and (3) 0.1 level of significance. The multiple R2 and r.m.s.e. were not changed by the inclusion of S2/R in men. However, the inclusion of S2/R changed the R2 from 0.73 to 0.81 and the r.m.s.e. from 3.83% to 3.22% in women. Cross-validation of the equations that included S2/R showed the accuracy of prediction (coefficient of variation, 0.23 for men; 0.16 for women) was approximately the same as for the validation group. These findings indicated that the addition of S2/R to selected anthropometric variables significantly improved the prediction of %BF for women, but not for men