Usability of classic and specific bioelectrical impedance vector analysis in measuring body composition of children

In this study, we aimed to analyse the relationship between body composition and bioelectrical variables in children and adolescents. The sample was composed of 6801 individuals (4035 males; 2766 females) aged 8-20 years included in the National Health and Nutrition Examination Survey (NHANES) years 1999-2004. Classic and specific bioelectrical impedance vector analysis (BIVA) were applied and compared with dual-energy X-ray absorptiometry (DXA) for the evaluation of fat mass (FM) and fat-free mass (FFM), and bioimpedance spectroscopy (BIS) for the evaluation of intra-cellular water (ICW), extra-cellular water (ECW), and total body water (TBW). Fat-free mass index (FFMI) was calculated. Spearman's correlation, regression, and depth-depth analyses were applied. The evaluation of body composition with BIVA agreed well with that of DXA or BIS, independently of sex, age, and ethnicity: classic BIVA was mostly sensitive to differences in TBW, ECW/ICW, whereas specific BIVA to differences in %FM, FFMI, and ECW/ICW. The depth-depth analysis confirmed the asso-ciations of classic BIVA (coeff. 0.500, p < 0.001), and specific BIVA (coeff. 0.512, p < 0.001), also considering the significant effect of age (p < 0.001). In classic BIVA the association was slightly stronger in females (by 0.03, p = 0.042) and among Blacks (0.06, p = 0.002), whereas in specific BIVA it was stronger by 0.06 (p < 0.001) in females and similar among ethnic groups. The combined use of the two BIVA approaches represents a valuable tool for complete evaluation of body composition in growth studies, for the prevention and monitoring of malnutrition, and the monitoring of the performance in young athletes. (c) 2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved

Protein in the Hospital: Gaining Perspective and Moving Forward

Provision of adequate protein is crucial for optimizing outcomes in hospitalized patients. However, the methodologies upon which current recommendations are based have limitations, and little is known about true requirements in any clinical population. In this tutorial, we aim to give clinicians an understanding of how current protein recommendations were developed, an appreciation for the limitations of these recommendations, and an overview of more sophisticated approaches that can be applied to better define protein requirements. A broader perspective of the challenges and opportunities in determining clinical protein requirements can help clinicians think critically about the individualized nutrition care they provide to their patients with the goal of administering adequate protein to optimize outcomes

Evaluation of dietary patterns among individuals submitted to bariatric surgery

Univ Fed Sao Paulo, Paulista Med Sch UNIFESP, Sao Paulo, BrazilUniv Minnesota Twin Cities, Minneapolis, MN USAHosp Clin UFPR, Bariatr Surg Serv, Curitiba, Parana, BrazilFed Univ Parana UFPR, Curitiba, Parana, BrazilUniv Fed Sao Paulo, Paulista Med Sch UNIFESP, Sao Paulo, BrazilWeb of Scienc

Bioelectrical Impedance Analysis Overestimates Fat‐Free Mass in Breast Cancer Patients Undergoing Treatment

Background: Bioelectrical impedance analysis (BIA) is commonly used to assess fat-free mass (FFM) and fat mass (FM) in breast cancer patients. However, because of the prevalence of overweight, obesity and variable hydration status in these patients, assumptions for existing prediction equations developed in healthy adults may be violated, resulting in inaccurate body composition assessment. Methods:We measured whole-body FFM using single-frequency BIA (50 kHz) and dual-energy x-ray absorptiometry (DXA) in 48 patients undergoing treatment for breast cancer.We applied raw BIA data to 18 previously published FFM prediction equations (FFMBIA) and compared these estimates to DXA (FFMDXA; reference method). Results: On average, patients were 52 ± 10 (mean ± SD) years of age and overweight (body mass index: 27.5 ± 5.5 kg/m2; body fat by DXA: 40.1% ± 6.6%). Relative to DXA, BIA overestimated FFM by 4.1 ± 3.4 kg (FFMDXA: 42.0 ± 5.9 kg; FFMBIA: 46.1 ± 3.4 kg). Individual equation-generated predictions of FFMBIA ranged from 39.6 ± 6.7 to 52.2 ± 5.6 kg, with 16 equations overestimating and 2 equations underestimating FFMBIA compared with FFMDXA. Based on equivalence testing, no equation-generated estimates were equivalent to DXA. Conclusion: Compared with DXA, BIA overestimated FFM in breast cancer patients during treatment. Although several equations performed better than others, none produced values that aligned closely with DXA. Caution should be used when interpreting BIA measurements in this clinical population, and future studies should develop prediction equations specific to breast cancer patients. (Nutr Clin Pract. 2019;00:1–12)Financial disclosure: This work was funded by a Canadian Institutes of Health Research grant, an Ontario Ministry of Research and Innovation Early Researcher Award, and the Canadian Foundation for Innovation (all to M. Mourtzakis)