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

Validity between dual-energy x-ray absorptiometry and bioelectrical impedance for segmental fat analysis and a novel low-cost model developed using anthropometry in young adults

BACKGROUND

Accurate body fat distribution assessment is essential for managing cardiovascular disease and metabolic disorders. Although several methods are available for segmental fat analysis, few studies have examined the validity of affordable methods such as Bioelectrical Impedance Analysis (BIA) against the reference method, Dual-Energy X-ray Absorptiometry (DXA). This study aimed to assess the validity of BIA as compared to DXA for segmental fat mass assessment, and to develop anthropometric multivariate regression models that offer a cost-effective alternative for health professionals in clinical and public health settings.

METHODS

Cross-sectional study that included 264 young adults (161 males, mean age = 23.04 ± 5.61 years; and 103 females, mean age = 22.29 ± 5.98 years). Segmental fat mass was measured using DXA and BIA, and anthropometric measurements were collected following the ISAK protocol.

RESULTS

Significant differences were found between DXA and BIA for segmental fat mass (p < 0.001). Sex significantly influenced the results (p < 0.05), while BMI and hydration status had no significant impacts. The Bland-Altman analysis revealed significant differences (p < 0.001) between BIA and DXA for fat mass in the upper and lower limbs. Trunk fat mass also differed significantly in males and females (p < 0.001), except for the overall sample (p = 0.088). Anthropometric multivariate regression models showed a high predictive accuracy for both females (R²=0.766-0.910; p < 0.001) and males (R²=0.758-0.887; p < 0.001). Key predictors of segmental fat mass included body mass (r = 0.606-0.867; p < 0.001), skinfold thickness (r = 0.688-0.893; p < 0.001), and waist girth (r = 0.883 - 0.810; p < 0.001). Peripheral skinfolds were highly predictive for upper and lower limbs, while waist girth was relevant for trunk fat mass.

CONCLUSIONS

DXA and BIA are not interchangeable for segmental fat analysis due to the significant differences observed. However, the anthropometric multivariate regression models developed provide a cost-effective and reliable alternative for predicting segmental fat mass in clinical settings where DXA is unavailable.

TRIAL REGISTRATION

Not applicable.

Anthropometric-based predictive equations developed with multi-component models for estimating body composition in athletes

PURPOSE

Body composition can be estimated using anthropometric-based regression models, which are population-specific and should not be used interchangeably. However, the widespread availability of predictive equations in the literature makes selecting the most valid equations challenging. This systematic review compiles anthropometric-based predictive equations for estimating body mass components, focusing on those developed specifically for athletes using multicomponent models (i.e. separation of body mass into ≥ 3 components).

METHODS

Twenty-nine studies published between 2000 and 2024 were identified through a systematic search of international electronic databases (PubMed and Scopus). Studies using substandard procedures or developing predictive equations for non-athletic populations were excluded.

RESULTS

A total of 40 equations were identified from the 29 studies. Of these, 36 were applicable to males and 17 to females. Twenty-six equations were developed to estimate fat mass, 10 for fat-free mass, three for appendicular lean soft tissue, and one for skeletal muscle mass. Thirteen equations were designed for mixed athletes, while others focused on specific contexts: soccer (n = 8); handball and rugby (n = 3 each); jockeys, swimming, and Gaelic football (n = 2 each); and futsal, padel, basketball, volleyball, American football, karate, and wheelchair athletes (n = 1 each).

CONCLUSIONS

This review presented high-standards anthropometric-based predictive equations for assessing body composition in athletes and encourages the development of new equations for underrepresented sports in the current literature.

High-intensity interval training is not superior to continuous aerobic training in reducing body fat: A systematic review and meta-analysis of randomized clinical trials

Background/Objective

Guidelines on obesity management reinforce regular exercise to reduce body fat. Exercise modalities, including high-intensity interval training (HIIT), appear to produce a similar effect to continuous aerobic training (CAT) on body fat. However, they have not addressed the chronic effect of HIIT vs. CAT on body fat assessed by dual energy X-ray absorptiometry (DEXA). Thus, we compared the effectiveness of CAT vs. HIIT protocols on body fat (absolute or relative) (%BF) and abdominal visceral fat reduction, assessed by DEXA, in adults with overweight and obesity.

Methods

We conducted a systematic review and meta-analysis of randomized clinical trials (RCTs) including both female or male adults with excess body weight. We performed searches in the databases MEDLINE (PubMed), EMBASE, Scopus, LILACS, Web of Science and Cochrane.

Results

In our analysis (11 RCTs), we found no greater benefit on %BF of HIIT vs. CAT (MD -0.55%, 95% CI -1.42 to 0.31; p = 0.209). As for abdominal visceral fat, no training modality was superior (SMD: -0.05, 95% CI -0.29 to 0.19; p = 0.997). Regarding secondary outcomes (body weight, BMI, VO2 max, glycemic and lipid profiles), HIIT shows greater benefit than CAT in increasing VO2 max and fasting blood glucose and reducing total cholesterol.

Conclusion

HIIT is not superior to CAT in reducing %BF or abdominal visceral fat in individuals characterized by excess weight. However, HIIT showed beneficial effects on cardiorespiratory fitness, total cholesterol and fasting blood glucose when compared to CAT.

Body composition and bone mineral density in athletes with a physical impairment

Background

The impact of the type and the severity of disability on whole-body and regional body composition (BC), and bone mineral density (BMD) must be considered for dietary advice in athletes with a physical impairment (PI). This study aimed to investigate the impact of the type and the severity of disability on BC, the pattern of distribution of fat mass at the regional level, and BMD in athletes with a PI.

Methods

Forty-two male athletes with spinal cord injury (SCI, n = 24; age = 40.04 ± 9.95 years, Body Mass Index [BMI] = 23.07 ± 4.01 kg/m²) or unilateral lower limb amputation (AMP, n = 18; age = 34.39 ± 9.19 years, BMI = 22.81 ± 2.63 kg/m²) underwent a Dual-Energy X-Ray Absorptiometry scan. Each athlete with a PI was matched by age with an able-bodied athlete (AB, n = 42; age = 37.81 ± 10.31 years, BMI = 23.94 ± 1.8 kg/m²).

Results

One-Way Analysis of Variance showed significant differences between the SCI, AMP and AB groups for percentage fat mass (%FM) (P < 0.001, eta squared = 0.440). Post-hoc analysis with Bonferroni’s correction showed that athletes with SCI had significantly higher %FM vs. the AMP and AB groups (25.45 ± 5.99%, 21.45 ± 4.21% and 16.69 ± 2.56%, respectively; P = 0.008 vs. AMP and P < 0.001 vs. AB). The %FM was also significantly higher in the AMP vs. the AB group (P < 0.001). Whole-body BMD was negatively affected in SCI athletes, with about half of them showing osteopenia or osteoporosis. In fact, the mean BMD and T-score values in the SCI group (1.07 ± 0.09 g/cm² and −1.25 ± 0.85, respectively) were significantly lower in comparison with the AB group (P = 0.001 for both) as well as the AMP group (P = 0.008 for both). The type of disability affected BC and BMD in the trunk, android, gynoid and leg regions in SCI athletes and the impaired leg only in AMP athletes.

Conclusions

In conclusion, the type of disability and, partly, the severity of PI impact on BC and BMD in athletes with a PI. Nutritionists, sports medicine doctors, clinicians, coaches and physical conditioners should consider athletes with SCI or AMP separately. Athletes with a PI would benefit from specific nutrition and training programs taking into account the type of their disability.