Evidences concerning the importance of body composition (BC) have grown rapidly in the last few years [1-3]. Identifying physiological or pathological BC changes at limbs relies primarily on the availability of simple and accurate methods for estimating body compartments, secondly on knowledge of regional fat mass (FM) and non-bone lean mass (LM) in healthy people of different age and gender to be used as reference standard. This data on healthy subjects from the general population is almost completely missing. Only a small number of studies...

Study design and population Italian volunteers were enrolled with selective standards, representing the state of "health", divided by gender into two groups (125 males and 125 females; total: 250 persons). The inclusion criteria were fitness for blood donation, normal glycemic and lipid profiles, normal hepatic and renal function, the absence of any relevant past or present diseases, stable weight in the last year and body mass index (BMI) between 18 and 30 Kg/m2. Subjects with aberrant habits (i.e. smokers > 20 cigarettes/die, alcoholism etc.), pregnant...

ALMI and the anthropometric features of the studied population are presented in Table 1, as well as the percentage of patients regularly performing physical activity (and the weekly frequency).Table 2shows the descriptive statistics for all DXA parameters and indexes (including normalization of data per area) in both men and women (right and left segmental upper limbs – right and left segmental lower limbs – right and left total upper and lower limbs). No statistically significant difference was recorded between LM of right and left lower...

In our study AC and ThC showed significant statistical correlations with FM and LM of both total and segmental upper and lower extremities, respectively (Table3-4). Nevertheless, the analysis focused on lower limbs highlighted a gender-based difference for the predictive value of lower extremity anthropometric measures (ThC): the best correlation was proved for LM in males and FM in females (Table3). Regression analysis for AC did not demonstrate a difference between sexes showing the best correlation for FM in both males and females (Table4). Our results...

1. Gallagher D, Shaheen I, Zafar K (2008) State-of-the-art measurements in human body composition: A moving frontier of clinical importance. International journal of body composition research 6 (4):141-148 2. Thibault R, Pichard C (2012) The evaluation of body composition: a useful tool for clinical practice. Annals of nutrition & metabolism 60 (1):6-16. doi:10.1159/000334879 3. Bazzocchi A, Diano D, Ponti F, Salizzoni E, Albisinni U, Marchesini G, Battista G (2014) A 360-degree overview of body composition in healthy people: relationships among anthropometry, ultrasonography, and dual-energy x-ray...