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Anthropometric Prediction of DXA-Measured Percentage of Fat Mass in Athletes With Unilateral Lower Limb Amputation

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.

SUBMITTER: Cavedon V

PROVIDER: S-EPMC7786292 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe relevance of body composition (BC) to performance in sport has long been appreciated with special concern on the total and regional proportion of fat and muscle. Dual-energy X-ray absorptiometry (DXA) is able to accurately measure BC, but it may not be easily available in practice; anthropometry has long been used as a simple and inexpensive field method to objectively assess BC. The aim of this study was twofold: first, to develop and validate a sport-specific anthropometric predictive equation for total body fat mass (FM) and lean mass components in female handball players to be used in the sport setting; second, to cross-validate in female team handball players several independently developed, predictive equations for BC in female athletes.MethodsA total of 85 female team handball players (30 wings, 31 backs, 14 pivots, 10 goalkeepers) of different competitive levels underwent anthropometry and a whole-body DXA scan. Multiple linear regression analysis was used to develop predictive equations in a derivation sample (n = 60) of randomly selected players using demographic and anthropometric variables. The developed equations were used to predict DXA outcomes in an independent validation sample (n = 25).ResultsStatistically significant (P < 0.001) models were developed for total body FM (adjusted R 2 = 0.943, standard error of the estimate, SEE = 1,379 g), percentage FM (adjusted R 2 = 0.877, SEE = 2.00%), fat-free soft tissue mass (FFSTM) (adjusted R 2 = 0.834, SEE = 2,412 g), fat-free mass (FFSTM + bone mineral content; adjusted R 2 = 0.829, SEE = 2,579 g). All models were robust to collinearity. Each developed equation was successfully validated in the remaining 25 players using correlation analysis, mean signed difference, t-test, and Bland-Altman plot. The whole dataset of team handball players (n = 85) was used to cross-validate several predictive equations independently developed by others in female athletes. Equations significantly (P < 0.001 for all; t-test) over- or underestimated the corresponding DXA measurements.DiscussionIt is concluded that in team female handball players the anthropometric equations presented herein are able to estimate body fat and FFSTM with accuracy. Several BC predictive anthropometric equations developed in different female athletic populations revealed inaccurate when tested in team handball players. These results should be of use for coaches, physical trainers, and nutritionists when evaluating the physical status of female team handball players.

Project description:BackgroundTo evaluate cycling participation and identify barriers and facilitators related to cycling participation in people with a lower limb amputation (LLA) in the Netherlands.MethodsA questionnaire was sent to adults with a LLA between March and August 2019 to obtain information regarding prosthesis, individual's characteristics, amputation, cycling barriers and facilitators, and prosthetic satisfaction. The questionnaires were distributed via 8 orthopedic workshops, post and were given directly. To find cycling predictors, variables associated with cycling (p < 0.1) were entered into a logistic regression analysis. Non-significant variables were removed manually.ResultsParticipants (n = 207, 71% males) had a mean age of 62.0 ± 13.0 years. The most frequent level of amputation was transtibial (42%), and trauma was the most frequent cause of amputation (43%). After the LLA, 141 participants (68%) cycled for recreation (80%), physical fitness (74%), and transport (50%). In the past six months, cyclists cycled for recreation (79%) and transport (66%). Most cycled less than once a day. Recreational cyclists cycled alone (75%) for a median duration of 45 min or 14 km per ride. Cyclists with a transportation purpose usually cycled to go shopping (80%) or to visit friends (68%), with a median duration of 20 min or five kilometers per ride. Cyclists reported more facilitators (median (IQR) = 5 (3, 7) than non-cyclists 0 (0, 3). The majority of cyclists reported a positive attitude toward cycling (89%) and cycled because of health benefits (81%). A dynamic foot (odds ratio: 5.2, 95% CI 2.0, 13.3) and a higher number of facilitators (odds ratio: 1.3, 95% CI 1.2, 1.5) positively predicted cycling, whereas the presence of other underlying diseases (odds ratio: 0.4, 95% CI 0.2, 0.9) negatively predicted cycling (R2: 40.2%).ConclusionIn the Netherlands, the majority of adults cycled after a LLA, mainly for recreational purposes. A dynamic foot, a higher number of facilitators, and no other underlying diseases increases the likelihood of cycling after a LLA. The results suggest that personal motivation and a higher mobility level could be the key to increasing cycling participation. Future research should determine the association between motivation, mobility levels, and cycling with a LLA.

Project description:Lower extremity amputation is often performed in patients where both lower extremities are at risk due to peripheral arterial disease or diabetes, yet the proportion of patients who progress to amputation of their contralateral limb is not well defined. We sought to determine the rate of subsequent amputation on both the ipsilateral and contralateral lower extremities following initial amputation.We conducted a retrospective review of all patients undergoing lower extremity amputation (exclusive of trauma or tumor) at our institution from 1998 to 2010. We used International Classification of Diseases-Ninth Revision codes to identify patients and procedures as well as comorbidities. Outcomes included the proportion of patients at 1 and 5 years undergoing contralateral and ipsilateral major and minor amputation stratified by initial major vs minor amputation. Cox proportional hazards regression analysis was performed to determine predictors of major contralateral amputation.We identified 1715 patients. Mean age was 67.2 years, 63% were male, 77% were diabetic, and 34% underwent an initial major amputation. After major amputation, 5.7% and 11.5% have a contralateral major amputation at 1 and 5 years, respectively. After minor amputation, 3.2% and 8.4% have a contralateral major amputation at 1 and 5 years while 10.5% and 14.2% have an ipsilateral major amputation at 1 and 5 years, respectively. Cox proportional hazards regression analysis revealed end-stage renal disease (hazard ratio [HR], 3.9; 95% confidence interval [CI], 2.3-6.5), chronic renal insufficiency (HR, 2.2; 95% CI, 1.5-3.3), atherosclerosis without diabetic neuropathy (HR, 2.9; 95% CI, 1.5-5.7), atherosclerosis with diabetic neuropathy (HR, 9.1; 95% CI, 3.7-22.5), and initial major amputation (HR, 1.8; 95% CI, 1.3-2.6) were independently predictive of subsequent contralateral major amputation.Rates of contralateral limb amputation are high and predicted by renal disease, atherosclerosis, and atherosclerosis with diabetic neuropathy. Physicians and patients should be alert to the high risk of subsequent amputation in the contralateral leg. All patients, but particularly those at increased risk, should undergo close surveillance and counseling to help prevent subsequent amputations in their contralateral lower extremity.

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Anthropometric Prediction of DXA-Measured Percentage of Fat Mass in Athletes With Unilateral Lower Limb Amputation

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