Bioelectric Impedance Measures of Body Composition: Their Relationship with Level of Blood Pressure in Young Adults

There is evidence that increased body weight in adults is pre­dominantly due to an increase in the amount of fat. The association of blood pressure with body weight could be due to the increased total body mass or to some underlying relationship between blood pressure and body fat. The separate influences of body size and fatness on level of blood pressure in adults was investigated in a sample of 62 men and 51 women aged 18 to 30 years. Total body fatness, percent body fatness and fat-free mass were estimated using hydrostatic weighting and from equations using anthropometry in combination with measures of bioelectrical impedance. Our previous work in adults ages 18 to 49 years showed in both men and women a consistent positive correlation between level of systolic blood pressure and total body fat or percent body fat and no significant rela­tionship to fat-free mass. Women, but not men, showed a similar rela­tionship for diastolic blood pressure. In the present study, the results were less consistent. For diastolic blood pressure there were no significant rela­tionships observed with any of the measures of body composition. For sys­tolic blood pressure in the men, our findings were similar to those of the previous study for percent body fat and for total body fat. In the women, the relationships between fatness variables and blood pressure were not signifi­cant. However, contrary to the results of our previous study, a significant positive correlation was observed between fat-free mass and systolic blood pressure in both the men and the women. Components of body composition estimated from anthropometry in combination with bioelectric impedance are useful in epidemiological studies where underwater weighing is impractical

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