Determination Of Fat-free Mass Research Articles

Use of body mass index percentile to identify fat-free mass depletion in children with cystic fibrosis

Nutritional failure in children with cystic fibrosis (CF) has a negative effect on their morbidity and survival. It is unknown if determination of fat-free mass is a better screening method for nutritional failure than the currently recommended body mass index (BMI) alone. This cross-sectional study in 77 children with CF (age: 14.8±2.9y) measured fat-free mass, fat mass, bone mineral content and density using dual-energy X-ray absorptiometry. Nutritional failure was defined as BMI <10 percentile and/or fat-free mass index <5th percentile. Statistics were done using ANOVA and t-tests. Thirty-one percent (31%) of the patients with CF was characterized by nutritional failure, and 14% had low fat-free mass index with preserved values for BMI (hidden depletion). Only 52% of the patients with fat-free mass depletion was detected when using the criteria BMI <10 percentile. Patients with fat-free mass depletion had reduced values for forced expiratory volume in 1s (FEV(1)), independent of body mass index (P<0.05), and lower values for bone mineral density in whole body, spine and hip, and spine bone mineral apparent density (P<0.01). BMI ≤20 percentile was associated with a large drop in fat-free mass, a reduced FEV(1), and in bone mineral loss. Depletion of fat-free mass enhances morbidity in children with CF and is undetected in many of these children when only BMI percentile is used as screening method. BMI percentile of 20 should be considered as the new critical threshold for nutritional failure in CF if body composition techniques are not available.

Regional and total body bioelectrical impedance analysis compared with DXA in Icelandic elderly

The aims were (1) to compare fat free mass (FFM) estimates from regional hand-held bioelectrical impedance analysis (HHBIA) with conventional BIA (CBIA) and dual energy X-ray absorptiometry (DXA) and (2) to develop a population specific equation for FFM prediction in Icelandic elderly. DXA, CBIA and HHBIA data were available for 98 free-living Icelandic elderly (age=73.0 ± 5.6 years, body mass index=28.8 ± 5.2 kg/m(2)). Participants were randomized into a development block (n=50) and validation block (n=48). A population specific equation for FFM prediction was calculated using CBIA-derived resistance and anthropometric data from the development block and then compared with other BIA equations (Deurenberg, Segal, company-specific equations) and DXA estimates using the validation block. The correlations between BIA methods and DXA were very high, that is, >0.9; however, mean differences compared with DXA were quite variable, ranging from -5.0 (Deurenberg) to +2.5 (Segal, HHBIA) and +3.3 kg (CBIA). Mean difference of the population-specific equation was below 0.1 kg. The standard deviations of the differences ranged from 2.6 to 3.3 kg. The limits of agreement of the BIA methods were similar and between 9.9 and 12.9 kg. In Icelandic elderly, HHBIA and CBIA produce similar FFM estimates when using company-specific prediction equations. CBIA provides the additional possibility to use a population-specific prediction equation, which yields best results. However, limits of agreement were wide and similar of all employed BIA methods, which indicates principal limitations of BIA analysis in the determination of FFM.

COMPOSIÇÃO CORPORAL NOS CAVALOS DE TRABALHO

Determination of fat-free mass and fat mass in working horses may contribute to understanding the effects of training of these groups of horses. Also it could be used to improve the well-being of horses. The objective of this research was to evaluate the body composition of three different groups of horses (patrol [SER, n=18]; event [HIP, n=19]; inactive [INO, n=14]), submitted to a similar nutritional program but with different exercise level. It were evaluated the corporal mass, fat-free mass, fat mass, fat thickness, body score and age. And, to determine the body composition it was used the evaluation of body mass in association with fat thickness at rump by ultrasonography. The body mass, fat-free mass and age showed differences between groups (P Key words: Body composition, equine, exercise, fat-free mass.

Fat-free mass depletion in cystic fibrosis: Associated with lung disease severity but poorly detected by body mass index

Objective Malnutrition in cystic fibrosis (CF) is associated with poorer survival, but the determinants of fat-free mass (FFM) depletion are not well-characterized. It is unknown whether routine nutritional indicators, including body mass index (BMI), are adequate for detecting FFM depletion. This study aimed to determine the prevalence of FFM depletion in adults with CF, to compare fat-free mass index (FFMI) with BMI, and to identify predictors of FFM depletion. Methods This was a prospective cross-sectional study of 86 adults with CF (19–59 y old). Body composition was assessed using dual-energy X-ray absorptiometry to determine FFMI and BMI. FFMI percentiles and Z-scores were derived from a reference population of 156 healthy adults. FFM depletion was defined as an FFMI below the fifth percentile for age and gender and low BMI as <18.5 kg/m 2. Univariate and multivariate analyses identified predictors of FFMI and FFMI Z-score. Results Mean FFMIs were 18.3 ± 1.9 kg/m 2 in men with CF and 15.8 ± 1.1 kg/m 2 in women with CF ( P < 0.0005). FFM depletion was found in 14% of adults with CF, and low BMI was found in 18.6%. The sensitivity of BMI for detecting FFM depletion was 42%. Forced expiratory volume in 1 s as a percentage of predicted was independently associated with FFMI in women ( r = 0.62, P < 0.0001) and men ( r = 0.28, P = 0.045) and FFMI Z-score ( r = 0.41, P < 0.0001). Conclusion FFM depletion was found in 14% of adults with CF, but was undetectable by BMI in 58% of these patients. These findings, together with the association of FFMI with forced expiratory volume in 1 s predicted, suggest a role for body composition assessment in adult CF care.

A Comparison of Organ-Tissue Level Body Composition between College-Age Male Athletes and Nonathletes

The purpose of this study was to compare the characteristics of skeletal muscle (SM) mass and internal organ (liver and kidney) mass in resistance and/or high intensity trained collegiate athletes with nonathletes, and to examine the relationships between fat-free mass (FFM) and its major components of SM, liver mass, and kidney mass. Fifteen athletes and seventeen nonathletes volunteered for the study. FFM was measured by two-compartment densitometry. Contiguous magnetic resonance imaging was used to obtain images from the first cervical vertebrae to the ankle joint (no inter-slice gap) for each subject, and SM, liver and kidney cross-sectional areas and organ-tissue volumes were determined. Organ-tissue volumes (cm (3)) were converted to mass (kg) by multiplying the volumes by the assumed constant density of the tissues. On average, athletes had greater FFM (69.1 kg) than the nonathletes (52.6 kg). SM, liver, and kidney masses in athletes (33.0 kg, 1.84 kg and 0.39 kg, respectively) were higher compared with nonathletes (23.5 kg, 1.39 kg and 0.31 kg, respectively). When the various determinants of FFM were expressed as ratios, it was determined that the ratio of SM mass to FFM was higher in athletes (47.7 %) than nonathletes (44.7 %), and the ratios of liver and kidney to FFM were similar for the two groups (2.6 % and 0.6 %, respectively, for athletes; and 2.7 % and 0.6 %, respectively, for nonathletes). A strong correlation between FFM and SM mass was observed in athletes and nonathletes and the slopes of these regression lines were almost identical and parallel. FFM was also significantly correlated with liver and kidney mass for both athletes and nonathletes. This study suggests that SM, liver, and kidney masses are increased by FFM accumulation in resistance and/or high intensity trained athletes.

Reference values of fat-free and fat masses by bioelectrical impedance analysis in 3393 healthy subjects

Determination of fat-free mass (FFM) and fat mass (FM) is of considerable interest in the evaluation of nutritional status. In recent years, bioelectrical impedance analysis (BIA) has emerged as a simple, reproducible method used for the evaluation of FFM and FM, but the lack of reference values reduces its utility to evaluate nutritional status. The aim of this study was to determine reference values for FFM, FM, and %FM by BIA in a white population of healthy subjects, to observe the changes in these values with age, and to develop percentile distributions for these parameters. Whole-body resistance of 1838 healthy white men and 1555 women, aged 15–64 y, was determined by using four skin electrodes on the right hand and foot. FFM and FM were calculated according to formulas validated for the subject groups and analyzed for age decades. This is the first study to present BIA-determined age- and sex-specific percentiles for FFM, FM, and %FM for healthy subjects, aged 15–64 y. Mean FM and %FM increased progressively in men and after age 45 y in women. The results suggest that any weight gain noted with age is due to a gain in FM. In conclusion, the data presented as percentiles can serve as reference to evaluate the normality of body composition of healthy and ill subject groups at a given age.

The relationship between aerobic exercise capacity and circulating IGF-1 levels in healthy men and women.

To determine whether aerobic capacity is associated independently with insulin-like growth factor-I (IGF-1) levels in healthy community-dwelling men and women. The Baltimore Longitudinal Study on Aging (BLSA). A cross-sectional analysis of data from the population-based cohort of the Baltimore Longitudinal Study of Aging (BLSA). We studied 181 men and 92 women aged 20 to 93 years, volunteers in the Baltimore Longitudinal Study on Aging (BLSA). Subjects were free of endocrine, renal, hepatic, gastrointestinal, or cardiac diseases, and they were taking no medications known to interfere with the growth hormone-IGF-1 axis. All subjects underwent a single measurement of serum IGF-1 in the fasting state, as well as peak VO2 determinations during maximal treadmill exercise testing performed within one visit of the IGF-1 determination. Dual energy X-ray absorptiometry (DEXA) scans were performed in a subset of 171 subjects (64 women and 107 men) for determination of fat free mass (FFM). In the pooled group of women and men, univariate regression analysis revealed that age was correlated strongly with decreasing IGF-1 levels (r = -0.53, P < .001) and with peak VO2r = -0.56, P < .001). IGF-1 levels were also significantly correlated with peak VO2 (r = 0.29, P < .001). There were no significant gender-related differences in these relationships. On multivariate analysis, age (beta = -0.54, P < .001), but not peak VO2 (P = -0.01, P = .840), remained strongly associated with IGF-1 levels. After adjustment of peak VO2 for FFM in subjects with DEXA scans, results were similar. These findings indicate that although both peak aerobic capacity and circulating IGF-1 levels decline with age, aerobic capacity is not independently related to circulating IGF-1 in healthy men and women across the adult life span.

Fat-Free Mass as a Function of Fat Mass and Habitual Activity Level

The best predictor of energy expenditure in man is the fat-free mass of the body. Fat-free mass explains most of the variation in resting metabolic rate and even in total metabolic rate under sedentary conditions. We studied possible determinants of fat-free mass as routes to influence energy metabolism. Existing data sets were analysed with observations on height, fat mass (FM), fat-free mass (FFM), and habitual level of physical activity (PA). PA was calculated from average daily metabolic rate (ADMR) as measured over 1-4-week intervals with 2H2(18)O and basal metabolic rate (BMR): PA = ADMR/BMR. Ninety-six subjects, 66 females and 30 males, from 7 different studies were included. FFM and FM were adjusted for height by taking its ratio to the square of height, in analogy with the body mass index. Subsequently, all analyses were corrected for origin of the data. In a regression analysis FM explained 53 and 40% of the variation in FFM in females and males, respectively. Adding PA to the model raised the explained variation in FFM in females to 62%. In contrast with females (r = 0.10, n.s.), there was an independent relationship between PA and FM in males (r = -0.41, p less than or equal to 0.05), such that a higher PA was related to a lower FM. In conclusion, FFM is a function of FM and PA. The absence of an effect of exercise training on FFM, i.e. additional exercise in weight-reduction programmes, is discussed.