SOMATODIAGNOSTICS AND BIOIMPEDANCOMETRY OF TEENAGERS INVOLVED IN SPORTS TOURISM

Changes in body composition and growth pattern after adenotonsillectomy in prepubertal children

BackgroundLeg muscle mass is related to development and progression of knee OA, and some studies suggested low leg muscle mass quantified by cross-sectional images of CT or MRI was related...

Objective: In addition to the hemodynamic load, other clinical and biochemical factors could contribute to the development of left ventricular (LV) hypertrophy in hypertensive patients. It is not clear, however, whether body composition in terms of fat and muscle mass is related to the LV mass and whether this relationship differs between genders. The aim of the study was to investigate the possible association between components of the body mass, as estimated by a bioimpedance analysis (BIA), and LV morphology and function in hypertension. Design and method: In 146 patients with essential hypertension (age 48 ± 13; 81 males; 49 never treated and 97 studied after drug wash-out of at least 2 weeks) we measured anthropometric and clinical variables, plasma insulin and fibrinogen levels, total body fat and free fat mass and body muscle mass by BIA, and performed conventional echocardiography Results: Men had higher systolic blood pressure and body free fat and muscle mass and lower total body fat mass than women. LV hypertrophy was detected according to consensus criteria in 42 (28%) patients who were older, had higher body mass index, blood pressure, total body fat mass and fibrinogen levels than patients without LV hypertrophy. In men, LV mass index was significantly and directly related to age, body mass index, blood pressure, and fibrinogen levels, whereas no relationship were observed with body fat composition. In women, LV mass index was directly related to body mass index, blood pressure, duration of hypertension, total body fat mass, and plasma insulin and fibrinogen levels. At multivariate regression analysis, LV mass index was related independently with age and blood pressure in men and with blood pressure, duration of hypertension, and fibrinogen levels in women Conclusions: LV mass index is related to body fat mass only in women, a relationship that is not independent and that appears to be mediated by higher plasma levels of insulin and fibrinogen.

Funding Acknowledgements Type of funding sources: None. Backround: Vitamin D is essential for the optimal function of many bodily systems and it is associated with various types of metabolic illnesses such as obesity, diabetes mellitus, insulin resistance, and cardiovascular diseases including hypertension. Decreased absorption of vitamin D may pose a risk for sarcopenia by affecting the lipid profile responses in metabolic syndrome (MetS). Purpose Our aim is to examine the relationship between vitamin D level and selected sarkopenia parameters such as muscle and fat mass, muscle strength, body composition, and walking speed in patients with MetS. Method 67 patients (mean age=50.3±7.69/years, F:51, M:16) aged 35-65 years and diagnosed with MetS (according to NCEP-ATP III criteria) were included in the study. Body mass index (BMI), muscle and fat mass of the participants were assessed using bioelectrical impedance analysis (TANITA). Waist and hip circumferences were measured. Right and left quadriceps muscle strength (J-Tech CommanderTM Muscle Tester) and grip strength (Jamar dynamometer) of the dominant hand (all patients were right dominant) were measured with dynamometer. Walking speed was calculated by dividing the distance walked by minutes in the 6-minute walking test. Results Of the patients, 9 (13.4%) were categorized as deficiency (<12 ng/mL), 10 (14.9%) had inadequacy (≥12 and <20 ng/mL) and 48 (71.6%) had sufficiency (≥ 20 ng/mL) level of vitamin D. There was a significant correlation between vitamin D level and body fat mass (r=-0.29, p=0.017), BMI (r=-0.29, p=0.014), hip circumference (r=-0.28, p=0.021) and left quadriceps muscle strength (r=-0.288, p=0.018). There was no correlation between vitamin D level, 6 minutes walking speed, body muscle mass, right quadriceps muscle strength and hand grip strength (p>0.05). Conclusion In this study, although vitamin D level was associated with left lower extremity muscle strength in patients with MetS, it was not associated with other sarcopenia parameters such as muscle mass, upper extremity muscle strength and walking speed. The relationship between vitamin D level, fat mass and body composition seen in our study may be due to altered lipid metabolism responses. We think that the effects of vitamin D on sarcopenia in MetS should be prospectively examined in a larger sample including elderly patients and considering the vitamin D intake.

Background Body Mass Index (BMI) has been recognized as a prognosticator for heart failure (HF) in that higher BMI relates to lower mortality. However, limited data are available whether body composition underneath BMI would further differentiate patients with a better or worse outcome, especially in those with lower or normal BMI. Purpose To investigate the characteristics of body fat and body muscle in HF patient groups with different BMI, and their impact on prognosis. Methods Between July 2021 and July 2022, hospitalized HF patients who were suitable for the examination underwent body composition analysis by using bioelectrical analyses (BIA) in the stable state after decongestion therapy and before discharge. Percentage of body fat (PBF) and percentage of body muscle (PBM) were calculated by dividing the mass of body fat, or body muscle, respectively. Patients were divided into underweight (<18.5kg/m2), normal weight (20-24.9 kg/m2), overweight/obese (≥25kg/m2) based on BMI, who were followed for 180 days for all-cause death. Results 127 consecutive patients with obtained data were finally enrolled (60±15 years, 70% males), including 20 (15.75%) underweight, 75 (59.06%) normal weight, and 32 (25.19%) overweight/obese. As shown in Table 1, As shown in Table 1, the body fat mass and muscle mass varied with BMI, though they showed a different rate of change. Compared with patients with normal weight, the fat and muscle mass in those overweight/obese was 81.8% and 12.4% higher; whereas it was 39.2%, and 23.1% lower in those underweight, respectively. As results, the overweight/obesity group had a higher PBF, but a lower percentage of PBM. Consequently, the overweight/obesity group had a higher PBF, a lower PBM and a decreased muscle mass/fat mass ratio (MFR); conversely, the underweight group had a lower PBF, a higher PBM and an increased MFR. During 180-day follow-up, 17 (13.4%) died for all cause. By Cox regression analysis, MFR independently predict all-cause death (HR, 1.273, 95% CI: 1.056-1.534, p=0.011) after adjusted for age, BMI, ejection fraction and NT-proBNP. Of note, in patients with normal weight, Receiver Operating Characteristic (ROC) curve analysis suggested the capability of MFR (AUC=0.780, p=0.003) as well as its superiority over BMI in association with all-cause mortality (Figure 1). Conclusions The change of body fat or muscle mass with BMI displayed a different rate in HF patients, so that the MFR was higher in underweight but lower in overweight/obese when compared to normal weight group. Apart from BMI, MFR emerged as a predictor of mortality, in particular in patients with normal weight.

Objective: Prolonged treatment with low doses of inhaled corticosteroids may affect the growth rate; however, limited data are currently available for body composition parameters in children with asthma. We examined whether treatment with inhaled corticosteroids has an effect on body mass index, basal metabolic rate, percentage body fat, obesity degree, fat mass, and muscle mass in children with mild asthma. Materials and Methods: The study was performed in 45 children with mild persistent asthma being treated with inhaled corticosteroids and 45 healthy controls. Body composition parameters; body mass index, percentage body fat, obesity degree, basal metabolic rate, body fat mass, muscle mass, and waist-hip circumferences were measured. Written questionnaires including duration of television/computer viewing, frequency of fast food consumption, and weekly physical activity were completed. Results: There was no difference in body composition parameters and waist-hip circumference measurements between the groups. A positive correlation was demonstrated between the duration of inhaled corticosteroid treatment and the percentage of body fat, muscle mass, fat mass, and hip circumference. When compared with healthy controls, a significant increase in the duration of television/ computer viewing and frequency of fast food consumption and a significant decrease in weekly physical activity were observed in children with asthma. Conclusion: Body composition parameters seem not to be affected in the inhaled steroid-using children with asthma. However, as the duration of inhaled corticosteroid treatment increased, the percentage of body fat, body fat mass, and hip circumference also increased. Children with asthma should be encouraged to increase physical activity and be recommended to decrease the duration of television/ computer viewing.

Effect of modified fasting therapy on body weight, fat and muscle mass, and blood chemistry in patients with obesity

Problem statement: The relationship between obesity and osteoporosis has been widely studied and epidemiological evidence shows that obesity is correlated with increased bone mass. Anthropometric factors such as body height and body weight which are related to body mass index should be considered. Approach: We measured whole body fat mass, fat free mass, muscle mass, Body water, percentage fat mass and body mass index in the South Indian women (n = 178, age = 38.34±13.59) by slim manager N-40 (Body Composition Analyzer, Korea). Bone mineral density was measured at right proximal femoral region of 50 South Indian women (n = 50, age = 50.12±13.73) using the device DPX Prodigy DXA Scanner, GE- Lunar, USA. Similarly, Bone mineral density of fore arm was measured using peripheral dual energy x-ra y absorptiometry (Osteometer, DTX-200 Ameritech Inc, USA) for 62 (39.76±13.41) women. Results: Body composition parameters such as body water, muscle mass, fat mass and fat free mass exhibited high significance with weight (p<0.001). Trochanter BMD demonstrated high significance with body water, fatfree mass and muscle mass (p<0.01). BMI displayed high significance with body fat mass (p<0.0001). Conclusion: So conclusion of this study depicts that the body composition parameters exhibited significant correlation with right femoral bone mineral density measured at various anatomical sites, but demonstr ated no correlation with right fore arm bone mineral den sity, similarly measured at anatomical sites.

IntroductionDigital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements.MethodsWe analysed 104 men aged 19–23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken.ResultsScanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements.ConclusionThe use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements. We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken. Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements. The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

Smoking cessation is associated with weight gain, but the effects of smoking cessation on measures of body composition (BC) have not been adequately evaluated. The purpose of this study is to examine the effects of 16 months of cigarette abstinence on areas of BC measured by dual-energy x-ray absorptiometry (DXA). One hundred fifty-two postmenopausal women participated in a smoking cessation study using the nicotine patch. Secondary analyses were conducted on data from 119 subjects (age 56 +/- 7 years, range 41-78 years) who had had DXA scans at baseline and 16 months later. Participants were classified either as quitters (self-reported cigarette abstinence confirmed with exhaled carbon monoxide [co] <or=8 ppm at 3 and 16 months after quit date) or as continued smokers. BC was assessed using a General Electric Lunar DXA IQ machine. Four areas of BC (kg) were measured: whole body weight, fat mass, muscle mass, and functional skeletal muscle mass in arms and legs (ASM/ht(2)). Multivariate analysis of covariance (MANCOVA) assessed changes in BC in quitters vs. continued smokers between baseline and 16 months of follow-up. Increases in BC measures were evaluated as a function of increased calorie intake or change in physical activity, using linear regression. Quitters significantly increased body weight (p < 0.001), fat mass (p < 0.001), muscle mass (p = 0.04), and functional muscle mass (p = 0.004) over time, when baseline BC measures and other confounding factors were controlled. Regression analysis indicated change in BC could not be accounted for by calorie intake or physical activity. Smoking cessation may be associated with increased fat and muscle mass in postmenopausal women. The novel finding of an increase in functional muscle mass suggests that smoking cessation could increase functional capacity. Further studies need to replicate these findings and examine mechanisms of these effects.

BackgroundSevere weight loss through means of bariatric surgery has been associated with loss of muscle mass due to lack of absorption of protein. The aim of this RCT is to investigate the effectiveness of protein supplementation in reducing the risk of developing protein malnutrition and muscle wasting in post-bariatric surgery patients in Qatar.Methods and analysisThe study was based at the Department of bariatric and metabolic surgery, Doha metropolitan and regional areas. It is envisaged that approximately 160 post-bariatric surgery patients will be randomized and followed up for 6 months. These will be males and females obese (BMI >35) Qatari patients between the aged 18–60 years. Subjects with renal or liver disease and those with past history of bariatric surgery will be excluded. By the completion of the trial, patients who took less than 80% of the supplement will be further excluded from the final analysis. Protein supplement (Cubitan,Protein, Nutricia, Netherlands) that contain daily intake of 20 g of protein to be taken orally 3 times a day throughout the study period. The placebo group will receive identical ampule containing zero-protein with exact instructions as per the intervention group. Body weight, muscle and fat mass, total protein, albumin, vit B12, Magnesium and Zinc will be measured at baseline and every follow up/study visit. Study variables will be compared between the 2 groups at different stages of the trial, including baseline, using Sample T-test (paired and unpaired) and the significance level will be confirmed with the 95% confidence interval with alpha error set to 0.05.Ethics and disseminationProtein supplementation for post-bariatric patients is not yet a standard procedure at Hamad Medical Corporation in Qatar and requires an RCT to establish evidence-based clinical practice guidelines. This study was approved by the Hamad Medical Corporation IRB and MRC committees (approval no. 16433/16).Trial registrationClinicalTrials.gov NCT03147456 (registration date: 18 April 2017).Strengths and limitations of this studyOne major strength of our study is that our population is a distinctive population (Qatari Obese patients) where results from international studies may not apply to the local and unique context. A local study like ours will provide healthcare providers in Qatar an opportunity to ensure good clinical practice and healthy and sustainable weight loss following bariatric surgery.The well-designed double-blinded RCT will almost certainly provide us with the evidence-based clinical practice guideline that we seek as health professionals.One limitation of our study is the slight discrepancy in caloric content of the intervention and the placebo (250 cal and 100 cal, respectively). However, it is the intervention that has the higher caloric content, in which case it may not influence the results in the direction of our hypothesis that protein supplementation leads to lower fat mass and higher muscle mass.Another limitation is that the use of the intervention and the placebo are not objectively measured. However, all efforts will be made to ensure compliance and reporting of consumption of products.A third limitation could be loss to follow up. Participants may cease to participate, particularly, once they have lost “sufficient’ weight and gained the fitness to consume any type of foods they desire. This is common in late stages of post-bariatric surgery (beyond 3 months). We feel that this may be a challenge, particularly in reference to our specific population. However, such findings albeit negative, should serve in improving the clinical practice delivered by healthcare providers.

OBJECTIVETo compare the effects of endurance and strength training and their combination on the body composition of high school students.METHODSSubjects (n=125) were randomized into endurance training (E), strength training (S), combined strength and endurance training (SE), or control group(C) for 18 weeks, 3 times/week, for 25 min. Bioelectrical impedance analysis were perform before and after training.RESULTSBody weight, BMI (Body Mass Index), body fat, body fat rate and muscle mass significantly decreased in E (both P&lt;0.01). Body weight, BMI, body fat and muscle mass significantly increased in S (both P &lt; 0.01), body fat rate increased significantly (P&lt;0.05). Body fat, body fat rate and muscle mass significantly decreased in SE (P &lt; 0.01). Body fat rate decreased significantly in C (P &lt; 0.01).CONCLUSIONEndurance training led to decrease in body weight, BMI, body fat, body fat rate and muscle mass. Strength training led to increase in body weight, BMI, body fat, body fat rate and muscle mass. Strength and endurance combination training led to decrease in body fat, body fat rate and muscle mass.Support or Funding InformationThe key lab of adolescent health intervention and exercise assessment

Aging is associated with significant changes in body composition, specifically a decrease in lean body mass and an increase in fat mass. These changes contribute to the prevalence of obesity and sarcopenia in the elderly population, impacting quality of life, morbidity and mortality. A complex interaction between hormonal decline, chronic inflammation, nutritional deficiencies, and reduced physical activity underlies these changes. This activity uses the PDCA (Plan-Do-Check-Act) methodology to screen for obesity and sarcopenia in the elderly at St. Mary's Church, Francis of Assisi. We use Bioelectrical Impedance Analysis (BIA) to measure body composition, which includes total body fat, visceral fat, subcutaneous fat, and muscle mass. Among 32 participants, the average total body fat, visceral fat, subcutaneous fat, and muscle mass were 36.5% each; 9.6%; 9.68%; and 21.5%. Body composition assessment using BIA is very important in managing the elderly's health. Preventive strategies, including tailored exercise programmes, nutritional counselling, and lifestyle modifications, are essential to maintain muscle mass and prevent excessive fat deposition, thereby improving quality of life and reducing morbidity and mortality. Keywords: Body Composition, Obesity, Sarcopenia, Elderly, Bioelectrical Impedance Analysis

BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population‐based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20–39 years without a previous history of CVD who underwent two health screening examinations during 2009–2010 and 2011–2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person‐years of follow‐up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82–0.91; aHR: 0.76, 95% CI 0.69–0.82, respectively] and women (aHR: 0.77, 95% CI 0.63–0.95; aHR: 0.75, 95% CI 0.59–0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10–1.22) and women (aHR: 1.32, 95% CI 1.06–1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between −1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80–0.92; aHR: 0.85, 95% CI 0.76–0.95) and women (aHR: 0.62, 95% CI 0.47–0.83; aHR: 0.59, 95% CI 0.44–0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10–1.25) and women (aHR: 1.64, 95% CI 1.20–2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.