Mauro Alexandre Páscoa

Body composition as a frailty marker for the elderly community

Background Body composition (BC) in the elderly has been associated with diseases and mortality; however, there is a shortage of data on frailty in the elderly. Objective To investigate the association between BC and frailty, and identify BC profiles in nonfrail, prefrail, and frail elderly people. Methods A cross-sectional study comprising 235 elderly (142 females and 93 males) aged ≥65 years, from the city of Amparo, State of São Paulo, Brazil, was undertaken. Sociodemographic and cognitive features, comorbidities, medication, frailty, body mass index (BMI), muscle mass, fat mass, bone mass, and fat percent (%) data were evaluated. Aiming to examine the relationship between BC and frailty, the Mann–Whitney and Kruskal–Wallis nonparametric tests were applied. The statistical significance level was P<0.05. Results The nonfrail elderly showed greater muscle mass and greater bone mass compared with the prefrail and frail ones. The frail elderly had greater fat % than the nonfrail elderly. There was a positive association between grip strength and muscle mass with bone mass (P<0.001), and a negative association between grip strength and fat % (P<0.001). Gait speed was positively associated with fat mass (P=0.038) and fat % (P=0.002). The physical activity level was negatively associated with fat % (P=0.022). The weight loss criterion was positively related to muscle mass (P<0.001), bone mass (P=0.009), fat mass (P=0.018), and BMI (P=0.003). There was a negative association between fatigue and bone mass (P=0.008). Discussion: Frailty in the elderly was characterized by a BC profile/phenotype with lower muscle mass and lower bone mass and with a higher fat %. The BMI was not effective in evaluating the relationship between BC and frailty. The importance of evaluating the fat % was verified when considering the tissue distribution in the elderly BC.

Minimum Time to Achieve the Steady State and Optimum Abbreviated Period to Estimate the Resting Energy Expenditure by Indirect Calorimetry in Healthy Young Adults

BACKGROUND The optimum abbreviated period for measurement by indirect calorimetry (IC) to estimate the resting energy expenditure (REE), including the acclimation period, in healthy individuals has not been established. This study aimed to determine the acclimation time required to achieve the REE steady state during a 30-minute IC measurement and to define the optimum abbreviated measurement period in the steady state to estimate the REE in healthy young adults. METHODS Thirty-nine volunteers (27 men and 12 women; age, 18-31 years) were recruited. The REE was obtained by IC over 30 minutes. Friedmans test was used to compare the coefficient of variation (CV%) among all 5-minute intervals (REE5). To compare the REE values obtained during the first REE5 interval in the steady state with the REE average values of the subsequent measurements, Student paired t test, linear regression, and Bland-Altman test were used. RESULTS The CV% of the first REE5 (mean ± standard deviation: 19.9% ± 13.2%) was significantly higher (P < .0001) than that of all other REE5 (second REE5: 7.4% ± 3.8%; third: 7.8% ± 5.2%; fourth: 7.1% ± 3.9%; fifth: 8.0% ± 5.7%; sixth: 8.0% ± 4.5%). No significant difference was found between the second REE5 and the REE average values of the last 20 minutes. The second REE5 explained 90% of the REE average of the last 20 minutes, with the 95% limits of agreement by the Bland-Altman test ranging from -142.92 to 150.44 kcal/d. CONCLUSION Ten minutes can be used as an abbreviated alternative for IC measurements in healthy young adults, and values of the first 5-minute interval should be discarded.

Validity of Bioelectrical Impedance Analysis to Estimation Fat-Free Mass in the Army Cadets

Background: Bioelectrical Impedance Analysis (BIA) is a fast, practical, non-invasive, and frequently used method for fat-free mass (FFM) estimation. The aims of this study were to validate predictive equations of BIA to FFM estimation in Army cadets and to develop and validate a specific BIA equation for this population. Methods: A total of 396 males, Brazilian Army cadets, aged 17–24 years were included. The study used eight published predictive BIA equations, a specific equation in FFM estimation, and dual-energy X-ray absorptiometry (DXA) as a reference method. Student’s t-test (for paired sample), linear regression analysis, and Bland–Altman method were used to test the validity of the BIA equations. Results: Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland–Altman. Predictive BIA equations explained 68% to 88% of FFM variance. Specific BIA equations showed no significant differences in FFM, compared to DXA values. Conclusion: Published BIA predictive equations showed poor accuracy in this sample. The specific BIA equations, developed in this study, demonstrated validity for this sample, although should be used with caution in samples with a large range of FFM.

Efeito de 13 semanas de treinamento físico militar sobre a composição corporal e o desempenho físico dos alunos da escola preparatória de cadetes do exército

INTRODUCTION: Armies from all over the world acknowledge the importance of good physical fitness for the performance of military duties. The Military Exercise Training (MET) attempts to provide assistance to this search for better physical fitness and performance. OBJECTIVE: To verifying the effect on the body composition and physical performance of the students at ESPCEX (Military School for Preparation of Army Cadets) after 13 weeks of MET. METHODS: The sample was formed by 287 male students from the ESPCEX, whose average age was 18.33 ±1.26. Such students accomplished a boarding school routine, having defined schedules, meals and activities from which they were only released during the weekends. The MET was accomplished five days a week and it comprised both aerobic and resistance training. Measurement of body mass, height, skinfold (triceps, abdominal and suprailiac) was accomplished during pre and post training periods, and the following tests were performed: 12-minutes-run, oblique sit up, arm push up and pull up. Fat percentage, fat-free body mass and fat body mass were calculated using the anthropometric data based on the Guedes 3 skinfold protocol. RESULTS: Significant reduction in fat body mass, fat percentage and in triceptal and abdominal skinfold, as well as increase in suprailiac skinfold and fat-free body mass was observed when anthropometric and body composition data were compared, during the initial and the final periods of training. Significant improvement also occurred in all prformed physical tests, in which better performance was achieved. CONCLUSION: The acquired data suggest that performance of MET 5 days a week brought significantly improved body composition as well as physical performance

Accuracy of Bioelectrical Impedance Analysis in Estimated Longitudinal Fat-Free Mass Changes in Male Army Cadets

Introduction Bioelectrical impedance analysis (BIA) is a practical and rapid method for making a longitudinal analysis of changes in body composition. However, most BIA validation studies have been performed in a clinical population and only at one moment, or point in time (cross-sectional study). The aim of this study is to investigate the accuracy of predictive equations based on BIA with regard to the changes in fat-free mass (FFM) in Brazilian male army cadets after 7 mo of military training. The values used were determined using dual-energy X-ray absorptiometry (DXA) as a reference method. Materials and Methods The study included 310 male Brazilian Army cadets (aged 17-24 yr). FFM was measured using eight general predictive BIA equations, with one equation specifically applied to this population sample, and the values were compared with results obtained using DXA. The students t-test, adjusted coefficient of determination (R2), standard error of estimation (SEE), Lins approach, and the Bland-Altman test were used to determine the accuracy of the predictive BIA equations used to estimate FFM in this population and between the two moments (pre- and post-moment). Results The FFM measured using the nine predictive BIA equations, and determined using DXA at the post-moment, showed a significant increase when compared with the pre-moment (p < 0.05). All nine predictive BIA equations were able to detect FFM changes in the army cadets between the two moments in a very similar way to the reference method (DXA). However, only the one BIA equation specific to this population showed no significant differences in the FFM estimation between DXA at pre- and post-moment of military routine. All predictive BIA equations showed large limits of agreement using the Bland-Altman approach. Conclusion The eight general predictive BIA equations used in this study were not found to be valid for analyzing the FFM changes in the Brazilian male army cadets, after a period of approximately 7 mo of military training. Although the BIA equation specific to this population is dependent on the amount of FFM, it appears to be a good alternative to DXA for assessing FFM in Brazilian male army cadets.