Breast cancer (BC) is the most common cancer diagnosed among women worldwide. Phase angle (PhA), a proxy measure of membrane integrity and function, has gained relevance in clinical practice and it has been suggested to be a prognostic and nutritional indicator. This systematic review aimed to explore PhA and its relationship with nutritional status and survival in BC patients. Four databases (PubMed, EMBASE, Web of Science, and CINAHL) were systematically searched until September 2021 for studies evaluating PhA in BC patients. A total of 16 studies met the inclusion criteria, where 11 were observational studies and 5 were interventional studies. Baseline PhA-value varied from 4.9 to 6.30 degrees, showing a great variability and heterogeneity across the selected studies. Available data suggested that PhA decreased by 5–15% after completing chemotherapy, and those effects might persist in the long term. However, the use of tailored nutritional and/or exercise programs during and after therapy could prevent PhA reduction and body derangement. High PhA values were found in women displaying a better nutritional status, while inconsistent data were found on survival. Therefore, further studies are needed to focus on the clinical relevance of PhA in BC patients, evaluating its association with disease outcomes and survival.

Background An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. Methods Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. Results One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). Conclusion In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

Objective: Phase angle (PA), a bioelectrical impedance analysis (BIA) parameter, has proven to be a proxy of body cell mass in athletes, but very few data are available on its segmental evaluation (upper and lower limbs). Therefore, we aimed to assess whether whole-body and segmental PA varied among elite male athletes of different sports and compared these to control groups. Additionally, we investigated its relationship with anthropometric and body composition parameters. Approach: Elite athletes practicing cycling, water polo and ballet dance aged 18–40 years underwent anthropometric and BIA measurements. PA (whole-body and upper and lower limbs) was considered as raw BIA variable. Data were also compared with healthy subjects with similar characteristics who served as control groups. Main results: Participants included three groups of male athletes: 18 cyclists (age 28.6 ± 3.4 years; weight 70.6 ± 5.4 kg; BMI 21.5 ± 1.4 kg m2), 20 water polo players (age 23.9 ± 4 years; weight 89.0 ± 5.2 kg; BMI 25.9 ± 1.9 kg m2) and 18 ballet dancers (age 19.2 ± 1.3 years; weight 63.3 ± 5.8 kg; BMI 20.8 ± 1.0 kg m2) and three groups of healthy control subjects each of which similar for general characteristics (one to one) to the previous ones. Both whole-body and limb PAs were significantly higher in athletes compared to their respective controls, whereas no differences were found among sport groups. PA was positively correlated with BMI and fat-free mass (FFM) more in athletes than in controls and FFM was the main determinant. Significance: PA may represent a useful proxy parameter of soft tissue mass quality, directly related to physical activity level. Furthermore, the direct evaluation of segmental PA among athletes practicing different sports may be useful for assessing and monitoring the differences among athletes and changes due to training.

No abstract

Background Increased resting energy expenditure (REE) has been hypothesized to be a potential cause of weight loss in individuals with Crohn's disease (CD). This study aimed to develop and validate new predictive equations for estimating REE in adults with CD. Methods Adults, ages 18–65 years, with CD were recruited. Anthropometry, indirect calorimetry, and bioimpedance analysis were performed in all patients. Disease activity was assessed by Crohn's Disease Activity Index. The new predictive equations were generated using different regression models. Prediction accuracy of the new equations was assessed and compared with the most commonly used equations. Results A total of 270 CD patients (159 males, 111 females) were included and randomly assigned to the calibration (n = 180) and validation groups (n = 90). REE was directly correlated with weight and bioimpedance index, whereas the relation with both age and disease activity was inverse. The new equations were suitable for estimating REE at population level (bias: −0.2 and −0.3, respectively). Individual accuracy was good in both models (≥80%, respectively), especially in females; and similar results were shown by some of the selected equations. But, when accuracy was set within ±5%, the new equations gave the highest prediction. Conclusion The new, disease‐specific, equations for predicting REE in individuals with CD give a good prediction accuracy as far as those proposed in the literature for the general population. However, the new ones performed better at the individual level. Further studies are needed to verify the reliability and usefulness of these new equations.