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The psycho-functional decline of patients with AD is related to body composition variations, with a relative increase of fat mass with respect to the muscle component. The BIVA technique distinguished patients from controls and patients with different levels of cognitive decline. Therefore, it is a suitable tool for the screening and monitoring of nutritional status in Alzheimer's disease.

This review is directed to define the efficacy of bioelectrical impedance vector analysis (BIVA) for assessing two-compartment body composition. A systematic literature review using MEDLINE database up to 12 February 2014 was performed. The list of papers citing the first description of BIVA, obtained from SCOPUS, and the reference lists of included studies were also searched. Selection criteria included studies comparing the results of BIVA with those of other techniques, and studies analyzing bioelectrical vectors of obese, athletic, cachectic and lean individuals. Thirty articles met the inclusion criteria. The ability of classic BIVA for assessing two-compartment body composition has been mainly evaluated by means of indirect techniques, such as anthropometry and bioelectrical impedance analysis (BIA). Classic BIVA showed a high agreement with body mass index, that can be interpreted in relation to the greater body mass of obese and athletic individuals, whereas the comparison with BIA showed less consistent results, especially in diseased individuals. When a reference method was used, classic BIVA failed to accurately recognize FM% variations, whereas specific BIVA furnished good results. Specific BIVA is a promising alternative to classic BIVA for assessing two-compartment body composition, with potential application in nutritional, sport and geriatric medicine.

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The aim of this research was to validate a new procedure (SkanLab) for the three-dimensional estimation of total arm volume. SkanLab is based on a single structured-light Kinect sensor (Microsoft, Redmond, WA, USA) and on Skanect (Occipital, San Francisco, CA, USA) and MeshLab (Visual Computing Lab, Pisa, Italy) software. The volume of twelve plastic cylinders was measured using geometry, as the reference, water displacement and SkanLab techniques (two raters and repetitions). The right total arm volume of thirty adults was measured by water displacement (reference) and SkanLab (two raters and repetitions). The bias and limits of agreement (LOA) between techniques were determined using the Bland–Altman method. Intra- and inter-rater reliability was assessed using the intraclass correlation coefficient (ICC) and the standard error of measurement. The bias of SkanLab in measuring the cylinders volume was −21.9 mL (−5.7%) (LOA: −62.0 to 18.2 mL; −18.1% to 6.7%) and in measuring the volume of arms’ was −9.9 mL (−0.6%) (LOA: −49.6 to 29.8 mL; −2.6% to 1.4%). SkanLab’s intra- and inter-rater reliabilities were very high (ICC >0.99). In conclusion, SkanLab is a fast, safe and low-cost method for assessing total arm volume, with high levels of accuracy and reliability. SkanLab represents a promising tool in clinical applications.