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

High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

Training, Pharmacological Ergogenic Aids, Dehydration, and Nutrition Strategies during a Peak Week in Competitive Brazilian Bodybuilders: An Observational Cross-Sectional Study in a Non-World Anti-Doping Agency Competitive Environment

BACKGROUND

this observational and cross-sectional study aimed to describe training, pharmacological ergogenic aids, dehydration, and nutrition strategies during a peak week in competitive bodybuilders and monitor changes that occurred across this period.

METHODS

Ten amateur bodybuilders were followed during a peak week phase and one day post-contest. Training, diet, dehydration protocol, anabolic steroid use, and nonsteroidal agents were recorded, prescribed, and supervised by the same coach in charge. Body composition, resting metabolic rate, and circumferences were assessed by the research team.

RESULTS

Overall, during the peak week phase, the use of anabolic steroids, diuretics, and other pharmacological aids was high among athletes, and the dose and frequency were similar between competitors. Despite the use of supraphysiological doses of drugs, bodybuilders displayed a statistical reduction of lean mass markers, resting metabolic rate, and fat mass markers, possibly influenced by the performance of high volumes of aerobic exercise combined with dietary energy restriction.

CONCLUSIONS

The main findings of this study display that the coach in charge of Brazilian bodybuilders applied the same anabolic steroid, diuretic, and other pharmacological protocols for all competitors. Moreover, the protocols employed by bodybuilders did not fully attenuate the loss of lean mass during the peak week period.

Comparison of bioimpedance equations and dual-energy X-ray for assessment of fat free mass in a Chinese dialysis population

PURPOSE

Bioelectrical impedance analysis (BIA) is simple, noninvasive, inexpensive and frequently used for estimating fat free mass (FFM). The aims of this study were to evaluate the applicability of different BIA equations on FFM in Chinese subjects, and to compare the difference in hemodialysis and peritoneal dialysis patients with healthy controls respectively.

METHODS

Dialysis patients and healthy adults were enrolled in this study, and the subjects were matched by age, gender, and the minimum sample size in each group was calculated using PASS. FFM estimated by BIA was calculated using equations of Kyle, Sun SS and Segal, and TBW/0.73. Dual-energy X-ray absorptiometry (DXA) method was set as reference method. Pearson's correlation and Bland-Altman analysis were used to test the validity of the BIA equations.

RESULTS

50 hemodialysis (HD) patients, 52 peritoneal dialysis (PD) patients and 30 healthy adults aged 22-67 y were included in this study. Age, height, weight, BMI and gender did not differ significantly among HD, PD patients, and healthy controls (p > 0.05), but BIA parameters were quite different (p＜0.01). Bland-Altman analysis showed that in healthy volunteers, all equations showed good agreement with DXA measured. For dialysis patients, the FFM predictions of different equations showed differences between HD and PD patients, and the equations seemed more applicable for HD patients.

CONCLUSION

The equations developed by healthy subjects might be not appropriate for dialysis patients, especially peritoneal dialysis patients. It is recommended to develop a specific BIA equation from dialysis population.

Fat-free mass estimation in male elite futsal players: Development and validation of a new bioelectrical impedance-based predictive equation

OBJECTIVES

The present study aimed to develop and cross-validate a futsal-specific bioelectrical equation for estimating fat-free mass (FFM) in male players.

METHODS

A total of 66 futsal players (age 23.3 ± 5.4 years) from the Major Portuguese Futsal League "LIGA PLACARD" and from the 2nd and 3rd National Futsal Leagues were included in this cross-sectional, observational study. The participants underwent a foot-to-hand bioelectrical impedance analysis (BIA) at 50 kHz and completed a dual-energy X-ray absorptiometry (DXA) scan for reference body composition data. The sport-specific model was developed by stepwise multiple regression using bioelectrical raw parameters [resistance (R) and reactance (Xc)] as independent variables. Validation was performed using the PRESS approach, least squares regression, concordance correlation coefficient (CCC) and Bland-Altman analyses.

RESULTS

A BIA-based model was developed for FFM [FFM (kg) = -8.865 + 0.437 * Body Mass (kg) + 0.186 * Xc + 0.415 * stature (cm)²/R (R² = 0.89, standard error of estimation = 2.38 kg)]. Results showed a substantial strength of agreement (CCC = 0.953), an r² of 0.88 with a standard error of estimation equal to 2.31 kg, no mean bias (0.04 kg, p>0.05), low limits of agreement (ranged from -4.5 to 4.6 kg), and no trend (r = -0.170, p = 0.172).

CONCLUSIONS

The present equation is the first to allow for a valid, accurate, and sport-specific assessment of FFM in male futsal players.

Energy Balance, Hormonal Status, and Military Performance in Strenuous Winter Training

Severe energy deficit may impair hormonal regulation and physical performance in military trainings. The aim of this study was to examine the associations between energy intake, expenditure, and balance, hormones and military performance during a winter survival training. Two groups were studied: the FEX group (n = 46) had 8-day garrison and field training, whereas the RECO group (n = 26) had a 36-h recovery period after the 6-day garrison and field training phase. Energy intake was assessed by food diaries, expenditure via heart rate variability, body composition by bioimpedance, and hormones by blood samples. Strength, endurance and shooting tests were done for evaluating military performance. PRE 0 d, MID 6 d, POST 8 d measurements were carried out. Energy balance was negative in PRE and MID (FEX -1070 ± 866, -4323 ± 1515; RECO -1427 ± 1200, -4635 ± 1742 kcal·d^-1). In POST, energy balance differed between the groups (FEX -4222 ± 1815; RECO -608 ± 1107 kcal·d^-1 (p < 0.001)), as well as leptin, testosterone/cortisol ratio, and endurance performance (p = 0.003, p < 0.001, p = 0.003, respectively). Changes in energy intake and expenditure were partially associated with changes in leptin and the testosterone/cortisol ratio, but not with physical performance variables. The 36-h recovery restored energy balance and hormonal status after strenuous military training, but these outcomes were not associated with strength or shooting performance.

Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance

The bioelectrical impedance analysis (BIA) is one of the most commonly used techniques for assessing body composition in a clinical setting and in field approaches, as it has the advantages of easy application, fast, and non-invasive, in addition to its relatively low cost. However, the available predictive equations need to be valid for the evaluated subjects. The aim of this study was to verify the validity of several published BIA equations in estimating fat-free mass (FFM) among Brazilian adolescents, in addition to developing and cross-validating a BIA equation to estimate FFM appropriate for Brazilian adolescents. This is a cross-sectional study with 257 adolescents (128 girls) aged 10-19 years, randomly divided into two groups, namely, development (n = 172) and cross-validation (n = 85). The standard technique for assessing FFM was dual X-ray absorptiometry (DXA). The paired t-test, multiple regression, and the Bland-Altman plots were used to test the validity of the proposed models and to perform cross-validation of the model. The equation derived in this study was as follows: FFM = -17.189 + 0.498 (Height²/Resistance) + 0.226 Weight + 0.071 Reactance - 2.378 Sex + 0.097 Height + 0.222 Age; r ² = 0.92; standard error of the estimate = 2.49 kg; the new equation for FFM showed better agreement when compared with that of the equations developed in other countries. In conclusion, the newly developed equations provide a valid FFM estimation and are recommended for Brazilian adolescents with similar characteristics.

Changes in Body Composition, Energy Metabolites and Electrolytes During Winter Survival Training in Male Soldiers

The aim of this study was to examine changes in body composition, energy metabolites and electrolytes during a 10-day winter survival training period. Two groups of male soldiers were examined: the REC group (n = 26; age 19.7 ± 1.2 years; BMI 23.9 ± 2.7) had recovery period between days 6 and 8 in the survival training, whereas the EXC group (n = 42; age 19.6 ± 0.8 years; BMI 23.1 ± 2.8) did not. The following data were collected: body composition (bioimpedance), energy balance (food diaries, heart rate variability measurements), and biomarkers (blood samples). In survival training, estimated energy balance was highly negative: −4,323 ± 1,515 kcal/d (EXC) and −4,635 ± 1,742 kcal/d (REC). Between days 1 and 10, body mass decreased by 3.9% (EXC) and 3.0% (REC). On day 6, free fatty acid and urea levels increased, whereas leptin, glucose and potassium decreased in all. Recovery period temporarily reversed some of the changes (body mass, leptin, free fatty acids, and urea) toward baseline levels. Survival training caused a severe energy deficit and reductions in body mass. The early stage of military survival training seems to alter energy, hormonal and fluid metabolism, but these effects disappear after an active recovery period.

Body Composition Results of Caucasian Young Normal Body Mass Women in the Follicular Proliferative Phase, Measured for the Different Positions of Limbs

The bioelectrical impedance analysis (BIA) became a standardized technique for assessing body composition, but many factors affect the reproducibility of measurement, including body and limbs position. In spite of the fact that it is recommended for patient to be in a supine position, with arms abducted at least 30° and legs abducted at approximately 45°, a lot of authors conduct their measurements with arms and legs of patients separated to not touch the body but not strictly following the recommendations. Taking this into account, the aim of the study was to analyze the body composition results of Caucasian young normal body mass women in the follicular proliferative phase, measured for the different positions of limbs in order to compare the results obtained in the recommended position (with arms abducted at least 30° and legs abducted at approximately 45°) and in the commonly used position (not following strictly the recommendations). The study was conducted in a homogenous group of 100 adult females under the age of 30 years using BIA 101/ASE with the Bodygram Pro software and its equations by Akern Srl, Firenze, Italy, based on the measurement recommendations. The measurements were conducted (1) in a recommended position of arms abducted at least 30° and legs abducted at approximately 45° and (2) with arms spread and legs separated to not touch the body to compare the body composition assessment (fat mass, fat-free mass, body cell mass, muscle mass, water content, extracellular water content, and intracellular water content). It was stated that the results obtained for various positions of limbs were positively correlated (p < 0.0001; R > 0.5). At the same time, the statistically significant differences dependent on the position were observed for the calculated results of body cell mass (lower results for the recommended position for the results observed in kg and % of body mass; p = 0.0165 and p = 0.0075, respectively) and muscle mass (lower results for the recommended position for the results observed in kg and % of body mass; p = 0.0025 and p = 0.0011, respectively), as well as extracellular and intracellular water (higher % of total body water for the extracellular water and lower for intracellular water; p = 0.0049 and p = 0.0115, respectively), resulting from the measured resistance and reactance values. For all listed comparisons of significantly differing variables, weighted κ statistics indicated moderate agreement (values of 0.41–0.60), and the Bland–Altman plot analysis indicated no agreement (Bland–Altman index of >5%). While compared with the reference values, the major differences were observed for extracellular/intracellular water content, as, while applying a method with arms and legs separated to not touch the body (not recommended position), the extracellular water content was underestimated for 31% and intracellular water content was overestimated for 28% of participants. It may be concluded that the recommended body position of arms abducted at least 30° and legs abducted at approximately 45° should be chosen to ensure the reliability of the BIA measurements, as, while the recommendations of a body position are not followed, the results obtained may be misleading and may not reflect the actual body composition.

Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women

BACKGROUND/OBJECTIVES

Bioelectrical impedance is one of the most used clinical techniques to assess body composition; however, it is necessary that the available predictive equations are valid for the evaluated subjects. This study aimed to develop and cross-validate equations for fat-free mass (FFM) and lean soft tissue mass (LSTM) by bioelectrical impedance for Brazilian women, in addition to test the validity of other available equations.

SUBJECTS/METHODS

Cross-sectional study with 222 women aged 20-59 years, randomly divided into two groups: development and cross-validation. The standard technique for assessing fat mass, FFM and LSTM was dual energy X-ray absorptiometry. Paired t test, multiple regression, and Bland-Altman plots were used to test the validity of the proposed models, as well as to perform cross-validation of the models.

RESULTS

The equations derived in this study were: FFM = 16.284 + 0.442 × (Height²/Resistance) - 0.13 × age + 0.302 × Weight - 0.121 × Waist Circumference; r² = 0.86; SEE = 2.32 kg; and LSTM = 14.732 + 0.427 × (Height²/Resistance) - 0.125 × age + 0.291 × Weight - 0.115 × Waist Circumference; r² = 0.92; SEE = 2.29 kg. In addition, the new equation for FFM showed better agreement when compared to another equation developed for a Brazilian population.

CONCLUSIONS

The newly developed equations provide a valid FFM and LSTM estimation and are recommended for Brazilian women with similar characteristics.

Bioelectrical Impedance Phase Angle and Its Determinants in Patients with Classic Congenital Adrenal Hyperplasia

BACKGROUND

Patients with congenital adrenal hyperplasia due to 21-hydroxylase deficiency (CAH21OHD) have increased fat mass and metabolic alterations. The bioelectrical impedance phase angle (PhA) is an indicator of cellular integrity in several diseases. This study aimed to determine the influence of adiposity levels, sex, CAH21OHD, pubertal development, body composition, and treatment on the PhA of patients with CAH21OHD.

METHODS

Forty girls and 30 boys with CAH21OHD aged 15.3 ± 5.8 years were evaluated. Sexual maturation was assessed by a pediatrician. The PhA was assessed using bioelectrical impedance, percentage of fat mass (% FM), and lean soft tissue (LST) with dual-energy X-ray absorptiometry. Adiposity levels were compared using % FM tertiles and body mass index (BMI). Glucocorticoid dosage was converted using hydrocortisone dose equivalent (HDE).

RESULTS

No differences were found in the PhA values among the clinical form (p = 0.103), BMI (p = 0.498), and % FM (p = 0.654) groups. High PhA values were observed in boys (p = 0.011) and postpubertal (p < 0.001) patients. LST, HDE, and height in girls (r² = 0.68, p < 0.001) and age, HDE, and FM in boys (r² = 0.82, p < 0.001) determined the PhA variations. BMI explained 14% (p = 0.032) of the PhA variations, whereas LST, height, HDE, and FM (kg) explained 66% (p < 0.001) in the prepubertal, pubertal, and postpubertal groups, respectively.

CONCLUSION

LST determined the PhA variations in girls and the postpubertal group. Age and BMI were determinants in boys and the pre- and pubertal groups, respectively.

No differences in the body fat after violating core bioelectrical impedance measurement assumptions

Objective

It is unclear to what degree acutely violating bioelectrical impedance analysis (BIA) measurement assumptions will alter the predicted percent fat mass (%FM) and whether this differs by sex or body mass index (BMI).

Methods

%FM was assessed under control, dehydration, exercise, water, food intake and non-voided bladder conditions with three BIA devices (Tanita: BC-418, TBF-314, & Omron HBF-306CN) for men (n = 23, age: 24.0 ± 5.2 years old) and women (n = 17, age: 22.5 ± 3.4 years old) separately.

Results

For all BIA devices, there were no differences in the %FM values between the control and the other conditions in men or women (− 1.9 to 0.4%, p > 0.05). Across the three devices and five conditions, 97% of %FM tests returned values within 5% of control (2 tests), and 86% of tests were within 2% of control despite violating an assumption. The errors were greatest with dehydration and women were more likely to have a %FM difference greater than 2% than men with dehydration using the hand-to-foot device (Tanita TBF-314: 59% versus 9%). There were no differences in %FM between control and the conditions when examined by BMI (overweight/obesity: − 2.8 to 0.1% and normal weight: − 1.7 to 0.5%; BMI*trial, p = 0.99).

Conclusion

%FM estimates were similar despite acutely violating the preliminary measurement BIA assumptions across a range of different BMIs. The minor variations in %FM are smaller than what would be expected with day-to-day variability or weight loss intervention but may be larger in women than men.

Validity of bioelectrical impedance to estimate fat-free mass in boys with Duchenne muscular dystrophy

The evaluation of fat-free mass (FFM) in patients with Duchenne muscular dystrophy (DMD) is useful to investigate disease progression and therapeutic efficacy. This study aimed to validate the Bioelectrical impedance (BIA) method compared with the dual-energy X-ray absorptiometry (DXA) for estimating the %FFM in boys with DMD. This is a cross-sectional study performed with children and adolescents diagnosed with DMD. Resistance and reactance were measured with a BIA analyzer, from which eight predictive equations estimated the %FFM. The %FFM was also determined by DXA and its used as a reference method. Pearson correlation test, coefficient of determination, the root-mean-square error, the interclass correlation coefficient, and linear regression analysis were performed between %FFM values obtained by BIA and DXA. The agreement between these values was verified with the Bland-Altman plot analysis. Forty-six boys aged from 5 to 20 years were enrolled in the study. All the equations showed a correlation between the %FFM estimated by BIA and determined by DXA (p < 0.05). The Bland-Altman method indicated that two equations have a significant bias (p < 0.05) and six equations showed no significant bias of %FFM (p > 0.05). However, one of them has high variation and wide limits of agreement. Five of eight %FFM predictive equations tested in DMD were accurate when compared with the DXA. It can be concluded that BIA is a validity method to evaluate patients with DMD.

Comparison of Anthropometric Measures in US Military Personnel in the Classification of Overweight and Obesity

OBJECTIVE

This study aimed to determine (1) the level of agreement between BMI, circumference-based equation (CBE) measures, waist circumference (WC), and bioelectrical impedance analysis (BIA) measures and (2) whether BMI, CBE measures, or WC alone or in combination adequately reflects adiposity in military personnel compared with BIA.

METHODS

BMI from measured height and weight (using military overweight cutoffs in men [BMI ≥ 27.5 kg/m² ] and World Health Organization overweight cutoffs [BMI ≥ 25.0 kg/m² ]), BMI body fat percentage (BF%), WC, CBE BF%, and BIA BF% were collected. Respondents (N = 389, 78% men) were categorized with normal fat versus overweight, obesity, or overfat. Levels of agreement and standard screening performance measures were compared between anthropometric measures and BIA.

RESULTS

World Health Organization BMI and BIA BF% classified the most men and women with overweight/obesity; WC with BMI (BMI + WC) and WC alone classified the fewest men and women with overweight/obesity. Levels of agreement were all statistically significant and highest for BMI (men: Cohen's κ = 0.711; women: Cohen's κ = 0.814) and lowest for WC and BMI + WC (all Cohen's κ ≤ 0.270). BMI + CBE performed best overall (sensitivity = 50.9%, false discovery rate = 5.4%).

CONCLUSIONS

Our findings support BMI + CBE as an easy-to-implement combination to assess adiposity in the military.

[Relationship between pattern of food consumption and body composition in university students: a cross-sectional study]

Introduction

Introduction: young university students face a social dynamics that has generated complex lifestyles and, especially, an imbalance in the intake of macro and micronutrients, characterized by having a high caloric density intake, which results in significant excess of weight. It is unknown if these consumption patterns are related to body composition. This research aimed to determine the relationship between pattern of food consumption and body composition in university students. Method: an observational, descriptive, cross-sectional study with a sample of 189 students. Sociodemographic variables obtained by a survey, body composition variables obtained by bioimpedance, and food groups and their categories obtained via a 24-hour reminder method were included. A multinomial logistic regression model was performed to explain body composition according to consumption of food groups. Results: statistically significant associations were obtained between food consumption and body composition for visceral fat and consumption of eggs, meats, sausages and grains (p = 0.024), and consumption of sugars with bone mass (p = 0.029) and muscle mass (p = 0.013). The multiple regression model showed that sugar consumption increases the risk of having visceral fat (OR = 2.71), and increases the probability of being classified as an obese person (OR = 2.55). Consumption of eggs, meats, sausages, and grains favors an acceptable percentage of visceral fat (OR = 0.14). The consumption of fruits and vegetables increases the risk of having a high percentage of water (OR = 5.41), and low fat percentage (OR = 3.60). Conclusions: the consumption of sugars seems to have a close relationship with variables of body composition such as visceral fat, bone mass, and muscle mass. The consumption of fruits and vegetables was related to a low percentage of fat; however, their consumption is proportionally related to high levels of body water. Studies to establish associations between body composition and food consumption should be carried out taking into account specific intakes in order to establish a more accurate association.

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 student's t-test, adjusted coefficient of determination (R2), standard error of estimation (SEE), Lin's 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.

Muscle Mass in Children and Adolescents: Proposed Equations and Reference Values for Assessment

Objectives: The goal of this study was to develop regression equations to estimate LM with anthropometric variables and to propose percentiles for evaluating by age and sex. Methods: A cross sectional study was conducted with 2,182 Chilean students (1,347 males and 835 females). Ages ranged from 5.0 to 17.9 years old. A total body scan was carried out with the double energy X-ray anthropometry (DXA) to examine and measure lean muscle mass of the entire body. Weight, height, and the circumference of the relaxed right arm were also measured. Results: Four anthropometric equations were generated to predict lean mass for both sexes (R ² = 83-88%, SEE = 3.7-5.0%, precision = 0.90-0.93, and accuracy = 0.99). The Lambda-mu-sigma method was used to obtain the sex-specific and age-specific percentile curves of lean mass (p3, p5, p10, p15, p25, p50, p75, p85, p90, p95, and p97). Conclusion: The four proposed equations were acceptable in terms of precision and accuracy to estimate lean mass in children and adolescents. The percentiles were created by means of anthropometric equations and real values for DXA. These are fundamental tools for monitoring LM in Chilean children and adolescents of both sexes.

Can anthropometric, body composition, and bone variables be considered risk factors for musculoskeletal injuries in Brazilian military students?

Background

Musculoskeletal injuries are the main cause of premature discharge from military service and can sometimes lead to permanent disabilities. Some intrinsic risk factors are well discussed in the literature. However, the relation between body composition variables and the risk for musculoskeletal injury is not well known or recognized.

Methods

This prospective study evaluated 205 Brazilian military students. At the beginning of military service, health status and sports experience prior to military service were registered. Anthropometric variables were evaluated, and bone and body composition variables were measured using dual-energy X-ray absorptiometry. The occurrence of musculoskeletal injuries throughout the year was registered at the military physiotherapy service. At the end of 1 year of follow-up, risk factors were analysed by comparing the variables between the injured and non-injured students.

Results

No difference in previous health status was found between injured and non-injured groups, whereas sports experience prior to military service was identified as a protective factor (Odds Ratio (OR) 0.323; 95% CI: 0.108–0.968; p = 0.044). Anthropometric, bone, and body composition variables could not be identified as risk factors for musculoskeletal injuries in Brazilian military students.

Conclusion

Anthropometric, bone, and body composition variables could not be considered risk factors for musculoskeletal injuries in Brazilian military students.

Prediction equations for body composition of children and adolescents aged 8-19 years in Uganda using deuterium dilution as the reference technique

BACKGROUND AND AIMS

Body composition is important as a marker of both current and future health status. Bioelectrical impedance analysis (BIA) is a simple and accurate method for estimating body composition in field, clinical and research settings, if standard protocol procedures are followed. However, BIA requires population-specific equations since applicability of existing equations to diverse populations has been questioned. This study aimed to derive predictive equations for Total Body Water (TBW), Fat Free Mass (FFM) and Fat Mass (FM) determinations with BIA and anthropometric measurements in a population of children and adolescents aged 8-19 years in Uganda.

METHODS

A cross-sectional study was conducted among 203 children and adolescents aged 8-19 years attending schools in Kampala district (also referred to as Kampala city since the city is conterminous with the district), Uganda through a two-stage cluster sample design. Deuterium dilution method (DDM) was used as the reference measure while BIA and anthropometric measures were used to create the new body composition prediction equations through multivariate regression.

RESULTS

The new prediction equations explained 88%, 87% and 71% of the variance in TBW, FFM % and of FM respectively with no statistical shrinkage upon cross-validation. The linear regression models proposed in this study were well adjusted with respect to TBW, FFM and FM. Log of TBW obtained by DDM = 0.0129 × Impedance index + 0.0055 × Age + 0.0049 Waist Circumference + 0.1219Ht² + 2.0388. Log of FFM obtained by DDM = 0.0197 × FFM obtained by BIA - 0.0181 sex code - 0.00055 × Impedance + 3.1761. Log of FM obtained by DDM = 0.0634 × FM obtained by BIA - 0.1881 sex code + 0.0252 × Weight + 0.5273.

CONCLUSION

The use of these equations for more accurate body composition assessment may facilitate identification of effective intervention strategies to prevent or combat overweight and obesity among children and adolescents. They may also assist in treatment of conditions where more accurate information on body composition measures is required.

Diet Macronutrient Composition, Physical Activity, and Body Composition in Soldiers During 6 Months Deployment

Introduction

Optimal diet together with good physical fitness maintains readiness and military performance during longer deployments. The purpose of this study was to describe changes in dietary macronutrient and energy intake, total physical activity and body composition during a 6-month deployment in South Lebanon. Furthermore, associations of diet macronutrient intake and physical activity on body composition were also studied.

Materials and Methods

Forty male soldiers kept a 3-day food diary and their body composition was measured via bioimpedance and ultrasonography. Total physical activity was evaluated by accelerometers in a subgroup of participants. Measurements were conducted in the PRE-, MID-, and POST-deployment.

Results

Mean carbohydrate intakes were 39.5–42.6 E%, protein intakes 18.7–22.3 E%, and fat intakes 34.9–35.7 E%. Daily energy intake remained stable (10.1–10.3 MJ/D). Total physical activity was decreased during deployment (e.g., step count from 9,835 ± 2,743 to 8,388 ± 2,875 steps/day, p = 0.007). Skeletal muscle mass and subcutaneous fat increased by 1.3% (p = 0.019) and 1.9% (p = 0.006), respectively. Energy and fat intake associated positively with body mass and skeletal muscle mass (r = 0.31–0.48, p &lt; 0.05–0.001).

Conclusions

Carbohydrate intakes and physical activity were low, compared with the general recommendations. Protein intakes were relatively high. Skeletal muscle mass and subcutaneous fat increased. Suboptimal diet together with low level of physical activity may have a negative impact on body composition, physical performance, and cardiometabolic health. Consequently, soldiers should be encouraged to consume more fiber-rich carbohydrates and less saturated fatty acids as well as maintain a high level of physical fitness to sustain military readiness during long-term deployments.

Assessing the reliability of FTIR spectroscopy measurements and validity of bioelectrical impedance analysis as a surrogate measure of body composition among children and adolescents aged 8-19 years attending schools in Kampala, Uganda

Background

Accurate measurement of body composition in children and adolescents is important as the quantities of fat and fat-free mass have implications for health risk. The objectives of the present study were: to determine the reliability of Fourier Transform Infrared spectroscopy (FTIR) measurements and; compare the Fat Mass (FM), Fat Free Mass (FFM) and body fat percentage (%BF) values determined by bioelectrical impedance analysis (BIA) to those determined by deuterium dilution method (DDM) to identify correlations and agreement between the two methods.

Methods

A cross-sectional study was conducted among 203 children and adolescents aged 8–19 years attending schools in Kampala city, Uganda. Pearson product-moment correlation at 5% significance level was considered for assessing correlations. Bland Altman analysis was used to examine the agreement between of FTIR measurements and between estimates by DDM and BIA.. Reliability of measurements was determined by Cronbach’s alpha.

Results

There was good agreement between the in vivo D₂O saliva enrichment measurements at 3 and 4 h among the studied age groups based on Bland-Altman plots. Cronbach’s alpha revealed that measurements of D₂O saliva enrichment had very good reliability. For children and young adolescents, DDM and BIA gave similar estimates of FFM, FM, and %BF. Among older adolescents, BIA significantly over-estimated FFM and significantly under-estimated FM and %BF compared to estimates by DDM. The correlation between FFM, FM and %BF estimates by DDM and BIA was high and significant among young and older adolescents and for FFM among children.

Conclusions

Reliability of the FTIR spectroscopy measurements was very good among the studied population. BIA is suitable for assessing body composition among children (8–9 years) and young adolescents (10–14 years) but not among older adolescents (15–19 years) in Uganda. The body composition measurements of older adolescents determined by DDM can be predicted using those provided by BIA using population-specific regression equations.

Dual-energy x-ray absorptiometry metabolic maps to resting energy expenditure estimation, and body size dependence in Brazilian young men

OBJECTIVES

The model most suitable for estimating resting energy expenditure (REE) using dual-energy X-ray absorptiometry (DXA) metabolic maps is not known; moreover, the applicability in individuals with different body sizes also is uncertain. The aim of this study was to test the accuracy of REE estimation from models of DXA metabolic maps with four, five, and six tissue-organ components in young men, stratified by body size.

METHODS

We studied 52 young men between the ages of 18 and 29 y. Participants were clustered to small (SW; n = 32) and large (LW; n = 20) weight, and small (SWH; n = 25) and large (LWH; n = 27) weight-height. REE was measured by indirect calorimetry (REE_m), and predicted from DXA metabolic maps with four (REE_c1), five (REE_c2) and six (REE_c3) tissue-organ components.

RESULTS

REE_c1, REE_c2, and REE_c3 explained 54% (P < 0.001), 56% (P < 0.001), and 58% (P < 0.001) of REE_m variance in all participants, respectively. However, REE_c2 showed mean difference between REE_m (P < 0.001), and REE_c3 showed trends in estimating the REE (P < 0.05). In contrast, REE_c1 showed limits of agreement (95%) of -248.3 to 285.8 kcal/d, 18.7 ± 136.3 kcal/d of bias, and no trends in the Bland-Altman analysis. The relationship between all predicted models and measured REE decreased in LW and LWH.

CONCLUSIONS

REE_c1 can be considered the best accurate model of REE estimation in Brazilian young men, providing the REE and metabolically active tissue-organ of four components. Caution should be exercised with the use of DXA metabolic maps in populations with greater weight and greater weight-height.