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Objective: Obesity is characterized not only by an increase of fat mass but also by alterations in skeletal muscle. Bioimpedance analysis (BIA)-derived phase angle (PhA) may provide specific information on the inherent characteristics of fat-free mass, and is widely used as an index of poor nutritional status. The aim of this study was to describe whether and to what extent PhA varies depending on age, sex, and body mass index (BMI) in individuals with different weight status., Methods: We selected 1877 participants for this retrospective study (two weight status groups): 983 individuals with obesity (age 40 ± 13.9 y; BMI 39.5 ± 7.2 kg/m²) and 894 controls (age 40 ± 13.3 y; BMI 24.6 ± 2.7 kg/m²). Anthropometry and PhA at 50 kHz for the whole body were performed in all participants., Results: PhA was greater in men than in women, although a decline of PhA was observed with age, which was linear in women and occurred in men after 40 y of age. On the other hand, no significant differences were observed with increasing BMI in either sex; lower values might be observed when BMI >50 kg/m²., Conclusions: A more detailed appraisal of BIA-derived PhA in obesity is reported in the present study, providing basic data that might be taken into consideration in prevention and clinical nutrition. Further studies are needed to explore differences of PhA in individuals with different weight status., (Copyright © 2022 Elsevier Inc. All rights reserved.)

(1) Background: Gaucher disease (GD) is a rare lysosomal storage disease. The few studies analyzing Resting Energy Expenditure (REE) in GD involved mainly untreated patients and supported a hypermetabolic condition possibly due to the associated inflammatory state. Definitive conclusions could not be drawn also because of the heterogeneity and the small size of the samples investigated. In order to expand current knowledge concerning, in particular the condition of patients under Enzyme Replacement Therapy (ERT), we evaluated the nutritional status of a relatively large sample of GD patients followed at Federico II University Hospital in Naples, Italy. (2) Methods: The study, having a cross-sectional design and involving 26 patients on ERT, included routine biochemical analyses, bioelectrical impedance analysis, indirect calorimetry, and administration of food frequency and physical activity questionnaires. The results in GD patients were compared with those from an appropriate control group. (3) Results: GD patients had normal biochemical parameters in 80% of cases, except for HDL-cholesterol, consumed a hyper-lipidic diet, and had a 60% prevalence of overweight/obesity. Body composition did not differ between patients and controls; however, measured REE was significantly lower than predicted and was reduced in comparison with the healthy controls. (4) Conclusions: This study provided novel elements to the present knowledge about REE and the nutritional status of GD patients under ERT. Its results warrant confirmation in even larger GD population samples and a more in-depth investigation of the long-term effects of treatment superimposed on the basic pathophysiological disease condition.

Purpose: In patients living with Anorexia Nervosa (AN), dehydration and haemoconcentration, may prevent a correct interpretation of laboratory nutritional parameters. Our study aims to evaluate if some indicators of disease severity, as body mass index (BMI), Phase Angle (PhA) and months of amenorrhea may be predictors of metabolic alterations (serum albumin, liver enzymes)., Methods: In 154 outpatients with AN, case history was collected, and anthropometric and laboratory parameters measured. Patients were divided according to the following tertiles (T) of BMI, duration of amenorrhea and PhA: (1) BMI (T1 < 15.6; T2 15.6-16.8; T3 > 16.8 kg/m 2 ); (2) Amenorrhea duration (T1 < 7; T2 7-14; T3 > 14 months); (3) PhA value (T1 < 4.64; T2 4.64-5.35; T3: > 5.35°). ROC curves were used to determine which of these three indicators (BMI, PhA and amenorrhea duration) might better identify patients belonging to Group A or B (less than 3 or more metabolic abnormalities)., Results: The most frequent registered metabolic alterations were for alkaline phosphatase (ALP), alanine aminotransferase, cholesterol and hemoglobin. Aspartate aminotransferase, ALP and gamma glutamyl transferase abnormalities were frequent in the first tertiles of all the three indicators. Albumin was low in the T1 of BMI and PhA. No differences in nutritional alterations emerged according to amenorrhea duration. PhA had the best performance (AUCs: 0.721) in identifying patients with 3 or more abnormalities, with the optimal cut-off value of 4.5°., Conclusions: Our data confirmed PhA as the more reliable predictor of metabolic alterations, followed by BMI and amenorrhea duration, especially in the first tertile., Evidence-Based Medicine: Level 2., (© 2021. The Author(s).)

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/m 2 ) 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., (© 2021. The Author(s).)

Objective: Hand grip strength (HGS) is frequently used in clinical practice, resulting in a potential marker of nutritional status. This study aimed to develop reference values of HGS in Italian women with different categories of body mass index (BMI). Additionally, the main predictors of HGS were identified., Methods: A cross-sectional study was conducted in Italian women between ages 16 and 55 y with different categories of BMI at the Department of Clinical Medicine and Surgery, Federico II University Hospital, Naples Italy. The whole sample was divided into tertiles according to BMI: 15 to 17.29 kg/m 2 (T1), 17.3 to 19.9 kg/m 2 (T2), and 20 to 25 kg/m 2 (T3). Anthropometry, bioimpedance analysis, and muscle strength by an HGS test were evaluated. The cut-off values for HGS were developed for all participants and stratified by age group. Finally, a multivariate linear regression analysis was performed to assess the main predictors of HGS., Results: A total of 529 women with a mean age of 23.2 ± 7.0 y and an average BMI of 18.9 ± 2.5 kg/m 2 were analyzed. HGS was higher for the dominant hand than for the non-dominant hand in all BMI tertiles. On both sides, according to age groups, HGS increased with increasing age in T1 and T3, whereas it increased in the women between ages 20 and 30 y in T2 only. Multivariate linear regression analysis showed that predictors of HGS varied according to tertiles. Specifically, we found that body weight (R 2  = 0.252) was the main predictor in T1, whereas phase angle (PhA) was the main determinant in both T2 (R 2  = 0.240) and T3 (R 2  = 0.216)., Conclusion: This study defined the normal reference values of HGS in Italian women with different BMI ranges, stratifying the sample group by age. Additionally, the main predictors of HGS were assessed for each BMI tertile. In primary malnutrition (T1), the main predictor of HGS was body weight, whereas in the other two tertiles (T2, T3), the PhA was the main predictor of HGS., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA)., Methods: Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC., Results: A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of <5% in estimating REE at the group level. Accuracy at the individual level was slightly higher for the new equations, especially for the equation based on raw BIA variables (men = 70.3%; women = 72.3%)., Conclusions: Compared to the equations in the literature, the new equations showed good accuracy at both the group and individual levels, with a slight improvement in individual accuracy for the formula including raw BIA variables. However, future research is required to verify the role of the raw BIA variables in predicting REE in subjects with normal weight and overweight., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

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 m 2 ), 20 water polo players (age 23.9 ± 4 years; weight 89.0 ± 5.2 kg; BMI 25.9 ± 1.9 kg m 2 ) and 18 ballet dancers (age 19.2 ± 1.3 years; weight 63.3 ± 5.8 kg; BMI 20.8 ± 1.0 kg m 2 ) 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.

Background: The assessment of body composition is central in evaluating athletes' nutritional status and the effects of training. The aim of this study was to evaluate body composition and the relation between bioimpedance phase angle (PhA) and muscular strength in elite female volleyball players., Methods: Twelve volleyball players (age 23.8±3.6 years; weight 63.0±5.1 kg; height 170±4 cm; BMI 21.9±1.3 kg/m2) and 22 non-athletic females, who served as a control group (age 23.6±2.0 years; weight 60.7±4.8 kg; height 167±5 cm; BMI 21.9±1.3 kg/m2), participating in the study. Skinfold thickness measures were used and segmental bioelectrical impedance analysis (BIA) was performed. Additionally, hand grip strength was used to evaluate muscular strength., Results: Volleyball players had lower FM and higher FFM than controls (FM(kg)=15.7±2.7 vs. 18.0±3.0, P=0.036; FM(%)=24.8±3.0 vs. 29.5±3.8, P=0.001; FFM(kg)=47.4±3.5 vs. 42.8±3.6, P=0.001). Both whole-body and segmental PhA were higher in volleyball players (P<0.05) than in controls, whereas no differences were observed for hand grip strength. A positive relation was found between hand grip strength and whole-body and upper limbs PhA in all subjects, resulting stronger in volleyball players (r=0.696, P=0.012 and r=0.821, P=0.001, respectively)., Conclusions: The data confirmed that body composition differed between volleyball players and non-athletic subjects. In addition, a strong correlation between PhA and hand grip strength in both volleyball players and in controls was found. However, further evaluations are needed to investigate the use of hand grip strength in sport performance.

Background & Aims: The assessment of body composition (BC) can be used to identify malnutrition in patients with Crohn's disease (CD). The aim of this study was to evaluate the nutritional status of CD patients by assessing BC, phase angle (PhA) and muscle strength. Differences in disease duration and medications were also considered., Methods: Consecutive adult CD patients aged 18-65 years were enrolled in this cross-sectional study. Disease activity was clinically defined by the Crohn's Disease Activity Index (CDAI) in the active and quiescent phases. All participants underwent anthropometry, BC and handgrip-strength (HGS) measurements; additionally, blood samples were taken. Data from CD patients were also compared with age-, sex- and BMI-matched healthy people., Results: A total of 140 CD patients with a mean age of 38.8 ± 13.9 years and a mean body weight of 64.9 ± 12 kg were recruited and compared to controls. The findings showed that all nutritional parameters, especially PhA and HGS, were lower in CD patients than in controls, and these parameters were substantially impaired as disease activity increased. Active CD patients had a lower body weight and fat mass than both the quiescent and control groups. PhA was negatively correlated with age (r = -0.362; p = 0.000) and CDAI (r = -0.135; p = 0.001) but was positively associated with fat free mass (FFM) (r = 0.443; p = 0.000) and HGS (r = 0.539; p = 0.000). Similarly, serum protein markers were lower in the active CD group than in the quiescent group (p < 0.05). Disease duration and medications did not significantly affect nutritional status., Conclusions: BIA-derived PhA is a valid indicator of nutritional status in CD patients, and its values decreased with increasing disease activity. Additionally, small alterations in BC, such as low FFM, and reduced HGS values can be considered markers of nutritional deficiency. Therefore, the assessment of BC should be recommended in clinical practice for screening and monitoring the nutritional status of CD patients., (Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The measurement of body composition (BC) represents a valuable tool to assess nutritional status in health and disease. The most used methods to evaluate BC in the clinical practice are based on bicompartment models and measure, directly or indirectly, fat mass (FM) and fat-free mass (FFM). Bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DXA) (nowadays considered as the reference technique in clinical practice) are extensively used in epidemiological (mainly BIA) and clinical (mainly DXA) settings to evaluate BC. DXA is primarily used for the measurements of bone mineral content (BMC) and density to assess bone health and diagnose osteoporosis in defined anatomical regions (femur and spine). However, total body DXA scans are used to derive a three-compartment BC model, including BMC, FM, and FFM. Both these methods feature some limitations: the accuracy of BIA measurements is reduced when specific predictive equations and standardized measurement protocols are not utilized whereas the limitations of DXA are the safety of repeated measurements (no more than two body scans per year are currently advised), cost, and technical expertise. This review aims to provide useful insights mostly into the use of BC methods in prevention and clinical practice (ambulatory or bedridden patients). We believe that it will stimulate a discussion on the topic and reinvigorate the crucial role of BC evaluation in diagnostic and clinical investigation protocols.

Background: The prevalence of anorexia nervosa among males is increasing but few data are available in the literature. This cross sectional study aims to evaluate resting energy expenditure (REE) and phase angle as a marker of qualitative changes of fat free mass (FFM) in three leanness groups as compared with control subjects., Methods: 17 anorectic (AN) males, 15 constitutionally lean (CL) individuals, 12 ballet dancers (DC), and 18 control (CTR) subjects were evaluated. REE was measured by indirect calorimetry (V max29- Sensormedics), and body composition was evaluated by bioimpedance analysis (BIA) at 50 kHz (DS Medica). Phase angle (a bioimpedance variable related to nutritional status) was used to evaluate differences in FFM characteristics between these three types of leanness., Results: REE, adjusted for FFM and fat mass (FM), were significantly higher in CL and lower in AN individuals (1783 ± 47 vs. 1291 ± 58 kcal, p < 0.05) compared to the other groups. Body composition was similar in AN and CL whereas dancers had the highest FFM (58.9 ± 4.8 kg, p < 0.05); anorectic males showed the lowest phase angle (5.8 ± 1.2 degrees vs. other groups, p < 0.05) and dancers the highest phase angle (7.9 ± 0.7 degree vs. other group, p < 0.05)., Conclusions: Our findings confirm that phase angle could be a useful marker of qualitative changes, above all in the field of sport activities. On the other hand, there is the need to further evaluate the relationship between resting energy expenditure, body composition and endocrine status in different conditions of physical activity and dietary intake.

This study aimed to develop and validate new predictive equations for resting energy expenditure (REE) in a large sample of subjects with obesity also considering raw variables from bioimpedance-analysis (BIA). A total of 2225 consecutive obese outpatients were recruited and randomly assigned to calibration ( n = 1680) and validation ( n = 545) groups. Subjects were also split into three subgroups according to their body mass index (BMI). The new predictive equations were generated using two models: Model 1 with age, weight, height, and BMI as predictors, and Model 2 in which raw BIA variables (bioimpedance-index and phase angle) were added. Our results showed that REE was directly correlated with all anthropometric and raw-BIA variables, while the correlation with age was inverse. All the new predictive equations were effective in estimating REE in both sexes and in the different BMI subgroups. Accuracy at the individual level was high for specific group-equation especially in subjects with BMI > 50 kg/m². Therefore, new equations based on raw-BIA variables were as accurate as those based on anthropometry. Equations developed for BMI categories did not substantially improve REE prediction, except for subjects with a BMI > 50 kg/m². Further studies are required to verify the application of those formulas and the role of raw-BIA variables for predicting REE.