Abstract
To date there is no anthropometric equation specific to athletes with unilateral lower limb amputation to estimate the percentage of fat mass (%FM). This study investigated the accuracy of a set of anthropometric equations validated on able-bodied populations to predict the %FM assessed by-means of dual-energy x-ray absorptiometry (DXA) in athletes with unilateral lower limb amputation. Furthermore, a predictive anthropometric equation specific to athletes with unilateral lower limb amputation was developed from skinfold thickness measurements using DXA as the reference method for the estimation of the %FM. Twenty-nine white male athletes with unilateral lower limb amputation underwent a DXA scan and an anthropometric assessment on the same day. The %FM, calculated through several existing anthropometric equations validated upon able-bodied populations, was compared with the DXA-measured %FM (%FM_DXA). Accuracy and agreement between the two methods was computed with two-tailed paired-sample t-test, concordance correlation coefficient, reduced major axis regression and Bland-Altman analysis. A stepwise multiple regression analysis with the %FM_DXA as the dependent variable and age and nine skinfold thicknesses as potential predictors was carried out and validated using a repeated 10-fold cross-validation. A linear regression analysis with the sum of nine skinfolds as the independent variable was also carried out and validated using a repeated 10-fold cross-validation. The results showed that the anthropometric equations validated on able-bodied populations are inaccurate in the estimation of %FM_DXA with an average bias ranging from 0.51 to −13.70%. Proportional bias was also found revealing that most of the anthropometric equations considered, tended to underestimate/overestimate the %FM_DXA as body fat increased. Regression analysis produced two statistically significant models (P < 0.001 for both) which were able to predict more than 93% of total variance of %FM_DXA from the values of four skinfold measurements (i.e., thigh, abdominal, subscapular and axillary skinfold measurements) or from the sum of 9 skinfolds. Repeated cross-validation analysis highlighted a good predictive performance of the proposed equations. The predictive equations proposed in this study represent a useful tool for clinicians, nutritionists, and physical conditioners to evaluate the physical and nutritional status of athletes with unilateral lower limb amputation directly in the field.
Highlights
Amputation is defined as the total or partial absence of bones and/or joints as a result of trauma, illness or congenital anomalies (Simim et al, 2013)
The t-test showed that only the average %FM obtained with the Eq_DWg (Durnin and Womersley, 1974) was similar to the average %FMDXA, while all other anthropometric equations were significantly different to the %FMDXA
The limits of agreement showed that 95% of the time, the Eq_DWg (Durnin and Womersley, 1974) produced %FM estimates that were between −3.8% less and 4.9% higher than the %FMDXA
Summary
Amputation is defined as the total or partial absence of bones and/or joints as a result of trauma, illness (e.g., bone cancer or diabetes) or congenital anomalies (Simim et al, 2013). After a lower-limb amputation, subjects undergo changes in their body composition including increased whole-body adiposity (Sherk et al, 2010) along with muscle atrophy and an increase in the amount of fat mass in the residual limb (Sherk et al, 2010). Such changes in body composition are associated with negative consequences from both a health (Anderson et al, 2013) and a performance perspective (Ozkan et al, 2012). An accurate assessment of body composition in athletes with unilateral lower limb amputation is of great importance in view of assessing their nutritional and training status, as well as monitoring the impact of dietary and training interventions
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