Bioimpedance and Dual-Energy X-ray Absorptiometry Are Not Equivalent Technologies: Comparing Fat Mass and Fat-Free Mass

INSCYD physiological performance software is valid to determine the maximal lactate steady state in male and female cyclists

Introduction

The maximal lactate steady state (MLSS) is defined as the highest workload that can be maintained without blood lactate accumulation over time. The power output at MLSS (PMLSS) is regularly implemented to define training zones, quantify training progress, or predict race performance. The gold standard methodology for MLSS determination requires two to five trials of constant-load exercise, which limits the practical application in training. The INSCYD software can calculate the PMLSS (PMLSSINSCYD) based on physiological data that can be obtained during a ∼1 h laboratory visit. However, to the best of our knowledge, the validity of the most recent software version has not yet been investigated. This study aimed to assess the validity of the software's calculations on PMLSS in cycling.

Methods

The data for this study were retrieved from two published scientific sources. Thirty-one cyclists (19 males, 12 females) performed a 15 s sprint to estimate the VLamax, a ramp test for the V ˙ O 2 max assessment, and two to five constant-load tests to determine the PMLSS. The INSCYD software was used to calculate the PMLSS based on the V ˙ O 2 max , VLamax, sex, body mass, and body composition.

Results

The PMLSSINSCYD was higher than the PMLSS in the entire sample (mean difference: 4.6 W, p < 0.05, 95% CI 0.8-8.3 W) and in men (mean difference: 6.6 W, p < 0.05, 95% CI 1.3-11.8 W), but not in women (mean difference: 0.8 W, n.s., 95% CI -3.7 to 5.3 W), which was within the typical error of the PMLSS estimations (∼3%). In 12 subjects (nine males, three females), the PMLSSINSCYD differed by 3.1-7.3% compared to the MLSS. The Pearson correlations between the measured PMLSS and the calculated PMLSS (PMLSSINSCYD) were very strong in men (r = 0.974, p < 0.001, 95% CI 0.933-0.99), women (r = 0.984, p < 0.001, 95% CI 0.931-0.996), and for the entire sample (r = 0.992, p < 0.001, 95% CI 0.982-0.996).

Discussion

In conclusion, the PMLSS can be accurately calculated using the INSCYD software, but it still requires advanced testing equipment to collect valid V ˙ O 2 max and VLamax data.

Body composition in adults born preterm with very low birth weight

BACKGROUND

Studies on body composition in preterm very low birth weight (VLBW < 1500 g) survivors are inconsistent and trajectories later in life unknown. We assessed body composition and its change from young to mid-adulthood in VLBW adults.

METHODS

We studied 137 VLBW adults and 158 term-born controls from two birth cohorts in Finland and Norway at mean age 36 years. Body composition was assessed by 8-polar bioelectrical impedance. We compared results with dual-energy x-ray absorptiometry measurements at 24 years.

RESULTS

In mid-adulthood, VLBW women and men were shorter than controls. Fat percentage (mean difference in women 1.1%; 95% CI, -1.5% to 3.5%, men 0.8%; -2.0% to 3.6%) and BMI were similar. VLBW women had 2.9 (0.9 to 4.8) kg and VLBW men 5.3 (2.7 to 8.1) kg lower lean body mass than controls, mostly attributable to shorter height. Between young and mid-adulthood, both groups gained fat and lean body mass (p for interaction VLBW x age>0.3).

CONCLUSION

Compared with term-born controls, VLBW adults had similar body fat percentage but lower lean body mass, largely explained by their shorter height. This could contribute to lower insulin sensitivity and muscular fitness previously found in VLBW survivors and predispose to functional limitations with increasing age.

IMPACT

In mid-adulthood, individuals born preterm with very low birth weight had similar body fat percentage but lower lean body mass than those born at term. This was largely explained by their shorter height. First study to report longitudinal assessments of body size and composition from young to mid-adulthood in very low birth weight adults. Lower lean body mass in very low birth weight adults could contribute to lower insulin sensitivity and muscular fitness and lead to earlier functional limitations with increasing age.

Development and validation of new bioelectrical impedance equations to accurately estimate fat mass percentage in a heterogeneous Caucasian population

Fat mass percentage (%FM) is frequently determined by nutritionists and personal trainers with bioelectrical impedance analysis (BIA) devices. The aims of the present study were: (1) to develop new regression equations using dual-energy X-ray absorptiometry (DXA) as the reference method for estimating %FM in a heterogeneous Caucasian population with a foot-to-hand device (BIA-101) and a hand-to-hand device (BIA-TELELAB) and (2) to compare the new equations with the manufacturers' equations. We hypothesized that the new equations would lead to more accurate estimations compared with DXA. A total of 218 healthy Caucasian participants aged 18 to 65 years were divided into a development group and a validation group. The accuracy of the different equations was assessed by mean differences, coefficient of determination, standard error of the estimate (SEE), intraclass correlation coefficients (ICC), and Bland-Altman plots. The proposed equation for BIA-101 explained 90.0% of the variance in the DXA-derived %FM, with a low random error (SEE = 2.98%), excellent agreement (ICC = 0.94), no fixed bias, and relatively low individual variability (5.86%). For BIA-TELELAB, the proposed equation explained 88.0% of the variance in the DXA-derived %FM, with a low random error (SEE = 3.27%), excellent agreement (ICC = 0.93), no fixed bias, and relatively low individual variability (6.37%). The results obtained for the manufacturers' equations confirm that these equations are not a good option for %FM assessment. As hypothesized, the new regression equations for BIA-101 and BIA-TELELAB devices can accurately estimate %FM in a heterogeneous Caucasian population with a broad age range.