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The ability of bioelectrical impedance analysis and anthropometry to predict fat mass and fat-free mass was compared in a sample of 82 male athletes from a wide variety of sports, using dual-energy X-ray absorptiometry (DXA) as the reference method. The percent fat measured by DXA was 10.9+/-4.9% (mean +/- s), and fat mass was predicted with a standard error of the estimate of 1.7 kg for skinfolds and 2.8 kg for bioelectrical impedance analysis (P < 0.001). Fat-free mass was predicted with a standard error of the estimate of 1.7 kg for anthropometry and 2.6 kg for bioelectrical impedance analysis (P < 0.001). Regression of various individual skinfolds and summed skinfolds, to examine the effect of skinfold selection combinations by stepwise regression, produced an optimal fat mass prediction using the thigh and abdominal skinfold sites, and an optimal fat-free mass prediction using the thigh, abdominal and supra-ilium sites. These results suggest that anthropometry offers a better way of assessing body composition in athletes than bioelectrical impedance analysis. Applying the derived equations to a separate sample of 24 athletes predicted fat and fat-free mass with a total error of 2.3 kg (2.9%) and 2.2 kg (2.7%), respectively. Combining the samples introduced more heterogeneity into the sample (n = 106), and the optimal prediction of fat mass used six skinfolds in producing a similar standard error of the estimate (1.7 kg), although this explained a further 4% of the variation in DXA-derived fat. Fat-free mass was predicted best from four skinfolds, although the standard error of the estimate and coefficient of determination were unchanged.

The effect of lipohypertrophy at injection sites on insulin absorption has been studied in 12 insulin-dependent diabetic patients. The clearance of 125I-insulin from sites with lipohypertrophy was significantly slower than from complementary nonhypertrophied sites (% clearance in 3 h, 43.8 +/- 3.5 +/- SEM) control; 35.3 +/- 3.9 lipohypertrophy, P less than 0.05). The degree of the effect was variable but sufficient in several patients to be of clinical importance. Injection-site lipohypertrophy is another factor that modifies the absorption of subcutaneously injected insulin.

1. Multi-frequency bio-impedance analysis has been used to estimate extracellular and total body water in a heterogeneous group of 43 surgical patients (23 males, 20 females). 2. Radioisotope-dilution methods were used for the measurement of extracellular and total body water. 3. Resistance and reactance were measured between wrist and ankle at frequencies from 5 kHz to 1 MHz. 4. Extracellular and total body water were estimated by multiple stepwise regression using the radioisotope values as the dependent variables. The parameters included in the regression were: resistance and reactance at each frequency, body habitus parameters, plasma albumin and plasma sodium. 5. The standard errors of the estimates between the measured and estimated values were 1.73 litres (coefficient of variation 9.6%) and 2.17 litres (coefficient of variation 6.0%) for extracellular and total body water, respectively. 6. These errors represent a useful improvement relative to those obtained from anthropometric estimates. However, the improvements relative to the use of a single frequency (50 kHz) are not clinically significant.

1. Measurements of extracellular and total body water provide useful information on the nutritional status of surgical patients and may be estimated from whole-body bio-impedance measurements at different frequencies. 2. Resistance and reactance were measured at 50 frequencies from 5kHz to 1MHz in 29 surgical patients (17 males, 12 females) with a wide range of extracellular to total body water ratios. 3. A fit to the spectrum of reactance versus resistance data gave predicted resistances at frequencies zero and infinity. Values of extracellular and total body water determined by this bio-impedance spectroscopy technique were regressed against values obtained from radioisotope dilution. The standard errors of the estimate were 1.8931 and 3.2591 respectively. 4. Resistance indices (height2/resistance) at selected frequencies gave the highest correlations with extracellular and total body water at 5kHz and 200kHz respectively, and prediction equations derived from multiple stepwise regressions also showed these to be the optimum frequencies. The standard errors of the estimate for this multi-frequency bio-impedance analysis method were 1.9371 and 2.6061 for extracellular and total body water respectively. 5. To assess the ability of the two methods to measure changes in extracellular and total body water, reproducibility was assessed from repeat measurements 10 min apart in a subgroup of 15 patients. Bio-impedance spectroscopy gave mean coefficients of variation for extracellular and total body water of 0.9% and 3.0% respectively. For multi-frequency bio-impedance analysis the corresponding coefficients of variation were 0.9% and 0.6%. 6. It is concluded that a simple impedance analyser operating at only two frequencies compares favourably with the more complex spectroscopy technique for the determination of extracellular and total body water in surgical patients.

For an eating disorder study over a period of 1 year, we measured total-body bone mineral using a Hologic QDR 1000W in a total of 157 subjects and observed anomalies that questioned the accuracy of such measurements. Using the recommended Enhanced software, a change in total bone mineral content (⌬BMC) correlated positively with a change in weight (⌬W; r ‫؍‬ 0.66), but a loss of weight was associated with an increase in bone mineral areal density (BMD; r ‫؍‬ 0.58), arising from a reduction in bone area (AREA). Both regressions were highly significant. The dominant factor in this relationship was a strong correlation between ⌬AREA and ⌬BMC, for all parts of the skeleton, r > 0.9, with a slope close to 1. This is implausible because bone area would not be expected to change. When Standard software was used, the slope of the ⌬BMC/⌬W correlation was steeper, but the ⌬BMD/⌬W regression became positive. An artefact of dual-energy X-ray absorptiometry processing was suspected, and phantom measurements were made. The phantom consisted of tissue-equivalent hardboard cut and stacked to form cylinders corresponding to the head, trunk, arms, and legs of a standard man. The skeleton was constructed from layers of aluminium sheet as an approximation of the average shape, BMD, BMC, and AREA in each region. When aluminium thickness was varied, BMD thresholds were found, approximately 0.4 g/cm 2 for the legs and 0.2 g/cm 2 for the arms. Above these, bone area rose fairly rapidly toward a plateau. At higher skeletal densities, the relationships between measured and true BMDs were close to linear, but slopes were less than unity, so that changes would be underestimated by 10 -30%. Increases of thickness of the soft tissue of the phantom lowered AREA slightly. Uniform fat proportion increases led to decreases in BMC and AREA, but lard wrapped in an annulus around the limbs led to spurious increases in BMC and AREA of a similar magnitude to those observed in vivo, while BMD fell slightly, although there had been no true change of bone variables. Similar results were obtained with lard around the limbs of a volunteer. Reanalysis of phantom scans using Standard software confirmed the software differences noted in vivo. The phantom measurements offer an explanation of the anomaly in vivo and demonstrate that, under different circumstances, change in both BMC and BMD can be wrongly recorded. We believe that no valid conclusions can be drawn from measurements by the Holgic QDR 1000W of bone changes during weight

Body mass index (BMI) was compared with percentage body fat (%Fat) measured by dual energy X‐ray absorptiometry (DXA) in 233 adolescent schoolgirl volunteers and 179 adult female patients. Repeat measurements were made on 67 of the adolescents and 51 of the adults. The correlations between BMI and %Fat were established from the 300 adolescent measurements and the 230 adult measurements. Although highly significant relationships were found between BMI and %Fat, only 58% of the variance in %Fat in adolescents and 66% in adults could be predicted by BMI. At the 95% confidence levels, a BMI of 20 kg m−2 can correspond to a range of 18–33% body fat in adolescents and 13–32% in adults. Without any change in BMI, an adolescent's percentage fat can change by as much as ‐3% to + 7%. For an individual adult the same BMI can correspond to changes in fat of ±5%. Since the strength of prediction of percentage body fat from BMI is poor, caution should be exercised in its use for eating disorders research. © 1995 by John Wiley & Sons, Inc.