873 resultados para Anthropometry and body composition
Resumo:
Body composition analysis is relevant to characterize the nutritional requirements and finishing phase of fish. The aim of this study was to investigate the relationship between ichthyometric (weight, total and standard length, density and yields), bromatological (fat, protein, ash and water content) and bioelectrical-impedance-analysis (BIA) (resistance, reactance, phase angle and composition indexes) variables in the hybrid tambatinga (Colossoma macropomum × Piaractus brachypomus). In a non-fertilized vivarium, 520 juveniles were housed and fed commercial rations. Then, 136 days after hatching (DAH), 15 fish with an average weight of 37.69 g and average total length of 12.96 cm were randomly chosen, anesthetized (eugenol) and subjected to the first of fourteen fortnightly assessments (BIA and biometry). After euthanasia, the following parts were weighed: whole carcass with the head, fillet, and skin (WC); fillet with skin (FS); and the remainder of the carcass with the head (CH). Together, FS and CH were ground and homogenized for the bromatological analyses. Estimates of the body composition and yields of tambatinga, with models including ichthyometric and BIA variables, showed correlation coefficients ranging from 0.81 (for the FS yield) to 1,00 (for the total ash). Similarly, models that included only BIA variables had correlation coefficients ranging from 0.81 (FS and CH yields) to 0.98 (for the total ash). Therefore, in tambatinga, the BIA technique allows the estimation of the yield of the fillet with skin and the body composition (water content, fat, ash, and protein). The best models combine ichthyometric and BIA variables.
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The objective of this study was to evaluate the effect of vaccination against GnRH on performance traits, pig behaviour and acute phase proteins. A total of 120 pigs (36 non-castrated males, NCM; 36 males to be vaccinated, IM; 24 castratedmales, CM; and 24 females, FE)were controlled in groups of 12 in pens with feeding stations allowing the recording of individual feed intake. The two vaccinations (Improvac®) were applied at a mean age of 77 and 146 days. All pigswere individually weighed every 3 weeks from the mean ages of 74 to 176 days and backfat thickness (BT) and loinmuscle depth (LD) were also recorded ultrasonically. Twelve group-housed pigs for each treatment were video recorded during 2 consecutive days at weeks 9, 11, 20, 21, 23 and 25 of age to score the number of inactive or active pigs in each treatment group by scan sampling. Aggressive behaviour by the feeder and away from the feeder, and mounting behaviour was also scored by focal sampling. Blood samples from 12 NCM, 12 CM and 12 IM were taken to determine the concentration of circulating acute phase protein Pig-MAP atweeks 1, 2, 4, 11, 13, 21 and 25 of age. After slaughter, the number of skin lesions on the left half carcasswas scored. IMpresented overall a higher growth rate and daily feed intake compared to NCM (Pb0.05),whereas their feed conversion ratios did not differ significantly. In comparison with CM, IM presented a better feed conversion ratio (Pb0.05), since their overall dailyweight gaindid not differ significantly, butIM ate less. Final leanmeat percentage of IM and CM was lower compared to that of NCM (Pb0.05). Activity, mounting and aggressive behaviour of NCM was higher than in IM, CM and FE after the second vaccination. Pig-MAP concentrationswere significantly elevated just after surgical castrationand after bothadministrations of the vaccine (Pb0.05), but concentrations subsequently decreased throughout time. Skin lesions of NCM were significantly higher compared to that of IM and FE (Pb0.05). The effects of vaccination were especially remarkable after the second dose, when the higher feed intake and lower activity of IM compared to NCMmight result in higher final body weight and more fat. Results from this study indicate that some welfare aspects such as a reduced aggression and mounting behaviour may be improved by vaccination against GnRH, together with productive benefits like adequate feed conversion ratio and daily weight gain.
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The present study assessed the relative contribution of each body segment to whole body fat-free mass (FFM) and impedance and explored the use of segmental bioelectrical impedance analysis to estimate segmental tissue composition. Multiple frequencies of whole body and segmental impedances were measured in 51 normal and overweight women. Segmental tissue composition was independently assessed by dual-energy X-ray absorptiometry. The sum of the segmental impedance values corresponded to the whole body value (100.5 +/- 1.9% at 50 kHz). The arms and legs contributed to 47.6 and 43.0%, respectively, of whole body impedance at 50 kHz, whereas they represented only 10.6 and 34.8% of total FFM, as determined by dual-energy X-ray absorptiometry. The trunk averaged 10.0% of total impedance but represented 48.2% of FFM. For each segment, there was an excellent correlation between the specific impedance index (length2/impedance) and FFM (r = 0.55, 0.62, and 0.64 for arm, trunk, and leg, respectively). The specific resistivity was in a similar range for the limbs (159 +/- 23 cm for the arm and 193 +/- 39 cm for the leg at 50 kHz) but was higher for the trunk (457 +/- 71 cm). This study shows the potential interest of segmental body composition by bioelectrical impedance analysis and provides specific segmental body composition equations for use in normal and overweight women.
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OBJECTIVE: To determine the influence of body weight, fat mass, and fat distribution on resting endogenous glucose production in healthy lean and overweight individuals. DESIGN: measurements were performed in the resting postabsorptive state in individuals receiving an unrestricted diet. SETTING: Institute of Physiology of Lausanne University. MEASUREMENTS: resting post absorptive glucose production, glycogenolysis and gluconeogenesis; resting energy expenditure and net substrate oxidation. RESULTS: Endogenous glucose production was positively correlated with body weight, lean body mass, energy expenditure and carbohydrate oxidation. Gluconeogenesis was positively correlated with net lipid oxidation and energy expenditure, and negatively correlated with net carbohydrate oxidation. No correlation with body fat or fat distribution was observed. CONCLUSIONS: Gluconeogenesis shows a large interindividual variability. Net lipid oxidation and not body fat appears to be a major determinant of gluconeogenesis.
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BACKGROUND/OBJECTIVES: (1) To cross-validate tetra- (4-BIA) and octopolar (8-BIA) bioelectrical impedance analysis vs dual-energy X-ray absorptiometry (DXA) for the assessment of total and appendicular body composition and (2) to evaluate the accuracy of external 4-BIA algorithms for the prediction of total body composition, in a representative sample of Swiss children. SUBJECTS/METHODS: A representative sample of 333 Swiss children aged 6-13 years from the Kinder-Sportstudie (KISS) (ISRCTN15360785). Whole-body fat-free mass (FFM) and appendicular lean tissue mass were measured with DXA. Body resistance (R) was measured at 50 kHz with 4-BIA and segmental body resistance at 5, 50, 250 and 500 kHz with 8-BIA. The resistance index (RI) was calculated as height(2)/R. Selection of predictors (gender, age, weight, RI4 and RI8) for BIA algorithms was performed using bootstrapped stepwise linear regression on 1000 samples. We calculated 95% confidence intervals (CI) of regression coefficients and measures of model fit using bootstrap analysis. Limits of agreement were used as measures of interchangeability of BIA with DXA. RESULTS: 8-BIA was more accurate than 4-BIA for the assessment of FFM (root mean square error (RMSE)=0.90 (95% CI 0.82-0.98) vs 1.12 kg (1.01-1.24); limits of agreement 1.80 to -1.80 kg vs 2.24 to -2.24 kg). 8-BIA also gave accurate estimates of appendicular body composition, with RMSE < or = 0.10 kg for arms and < or = 0.24 kg for legs. All external 4-BIA algorithms performed poorly with substantial negative proportional bias (r> or = 0.48, P<0.001). CONCLUSIONS: In a representative sample of young Swiss children (1) 8-BIA was superior to 4-BIA for the prediction of FFM, (2) external 4-BIA algorithms gave biased predictions of FFM and (3) 8-BIA was an accurate predictor of segmental body composition.
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OBJECTIVE: Low and high body mass index (BMI) values have been shown to increase health risks and mortality and result in variations in fat-free mass (FFM) and body fat mass (BF). Currently, there are no published ranges for a fat-free mass index (FFMI; kg/m(2)), a body fat mass index (BFMI; kg/m(2)), and percentage of body fat (%BF). The purpose of this population study was to determine predicted FFMI and BFMI values in subjects with low, normal, overweight, and obese BMI. METHODS: FFM and BF were determined in 2986 healthy white men and 2649 white women, age 15 to 98 y, by a previously validated 50-kHz bioelectrical impedance analysis equation. FFMI, BFMI, and %BF were calculated. RESULTS: FFMI values were 16.7 to 19.8 kg/m(2) for men and 14.6 to 16.8 kg/m(2) for women within the normal BMI ranges. BFMI values were 1.8 to 5.2 kg/m(2) for men and 3.9 to 8.2 kg/m(2) for women within the normal BMI ranges. BFMI values were 8.3 and 11.8 kg/m(2) in men and women, respectively, for obese BMI (>30 kg/m(2)). Normal ranges for %BF were 13.4 to 21.7 and 24.6 to 33.2 for men and women, respectively. CONCLUSION: BMI alone cannot provide information about the respective contribution of FFM or fat mass to body weight. This study presents FFMI and BFMI values that correspond to low, normal, overweight, and obese BMIs. FFMI and BFMI provide information about body compartments, regardless of height.
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The restoration of body composition (BC) parameters is considered to be one of the most important goals in the treatment of patients with anorexia nervosa (AN). However, little is known about differences between AN diagnostic subtypes [restricting (AN-R) and binge/purging (AN-BP)] and weekly changes in BC during refeeding treatment. Therefore, the main objectives of our study were twofold: 1) to assess the changes in BC throughout nutritional treatment in an AN sample and 2) to analyze predictors of BC changes during treatment, as well as predictors of treatment outcome. The whole sample comprised 261 participants [118 adult females with AN (70 AN-R vs. 48 AN-BP), and 143 healthy controls]. BC was measured weekly during 15 weeks of day-hospital treatment using bioelectrical impedance analysis (BIA). Assessment measures also included the Eating Disorders Inventory-2, as well as a number of other clinical indices. Overall, the results showed that AN-R and AN-BP patients statistically differed in all BC measures at admission. However, no significant time×group interaction was found for almost all BC parameters. Significant time×group interactions were only found for basal metabolic rate (p = .041) and body mass index (BMI) (p = .035). Multiple regression models showed that the best predictors of pre-post changes in BC parameters (namely fat-free mass, muscular mass, total body water and BMI) were the baseline values of BC parameters. Stepwise predictive logistic regressions showed that only BMI and age were significantly associated with outcome, but not with the percentage of body fat. In conclusion, these data suggest that although AN patients tended to restore all BC parameters during nutritional treatment, only AN-BP patients obtained the same fat mass values as healthy controls. Put succinctly, the best predictors of changes in BC were baseline BC values, which did not, however, seem to influence treatment outcome.
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A short overview is given on the most important analytical body composition methods. Principles of the methods and advantages and limitations of the methods are discussed also in relation to other fields of research such as energy metabolism. Attention is given to some new developments in body composition research such as chemical multiple-compartment models, computerized tomography or nuclear magnetic resonance imaging (tissue level), and multifrequency bioelectrical impedance. Possible future directions of body composition research in the light of these new developments are discussed.
Resumo:
Introduction: Growth is a central process in paediatrics. Weight and height evaluation are therefore routine exams for every child but in some situation, particularly inflammatory bowel disease (IBD), a wider evaluation of nutritional status needs to be performed. Objectives: To assess the accuracy of bio-impedance analysis (BIA) compared to the gold standard dual energy X-ray absorptiometry (DEXA) in estimating percentage body fat (fat mass; FM) and lean body mass (fat free mass; FFM) in children with inflammatory bowel disease (IBD). To compare FM and FFM levels between patients with IBD and healthy controls. Methods: Twenty-nine healthy controls (12 females; mean age: 12.7 ± 1.9 years) and 21 patients (11 females; 14.3 ± 1.3 years) were recruited from August 2011 to October 2012 at our institution. BIA was performed in all children and DEXA in patients only. Concordance between BIA and DEXA was assessed using Lin's concordance correlation and the Bland-Altman method. Between-group comparisons were made using analysis of variance adjusting for age. Results: BIA-derived FM% showed a good concordance with DEXA-derived values, while BIA-derived FFM% tended to be slightly higher than DEXA-derived values (table). No differences were found between patients and controls regarding body mass index (mean ± SD: 19.3 ± 3.3 vs. 20.1 ± 2.8 kg/m2, respectively; age-adjusted P = 0.08) and FM% (boys: 25.3 ± 10.2 vs. 22.6 ± 7.1%, for patients and controls, respectively; P = 0.20; girls: 28.2 ± 5.7 vs. 26.4 ± 7.7%; P = 0.91). Also, no differences were found regarding FFM% in boys (74.9 ± 10.2 vs. 77.4 ± 7.1%; P = 0.22) and girls (71.8 ± 5.6 vs. 73.5 ± 7.7%; P = 0.85). Conclusion: BIA adequately assesses body composition (FM%) in children with IBD and could advantageously replace DEXA, which is more expensive and less available. No differences in body composition were found between children with IBD and healthy controls.
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BACKGROUND: Intraabdominal adipose tissue (IAAT) is the body fat depot most strongly related to disease risk. Weight reduction is advocated for overweight people to reduce total body fat and IAAT, although little is known about the effect of weight loss on abdominal fat distribution in different races. OBJECTIVE: We compared the effects of diet-induced weight loss on changes in abdominal fat distribution in white and black women. DESIGN: We studied 23 white and 23 black women, similar in age and body composition, in the overweight state [mean body mass index (BMI; in kg/m(2)): 28.8] and the normal-weight state (mean BMI: 24.0) and 38 never-overweight control women (mean BMI: 23.4). We measured total body fat by using a 4-compartment model, trunk fat by using dual-energy X-ray absorptiometry, and cross-sectional areas of IAAT (at the fourth and fifth lumbar vertebrae) and subcutaneous abdominal adipose tissue (SAAT) by using computed tomography. RESULTS: Weight loss was similar in white and black women (13.1 and 12.6 kg, respectively), as were losses of total fat, trunk fat, and waist circumference. However, white women lost more IAAT (P < 0.001) and less SAAT (P < 0.03) than did black women. Fat patterns regressed toward those of their respective control groups. Changes in waist circumference correlated with changes in IAAT in white women (r = 0.54, P < 0.05) but not in black women (r = 0.19, NS). CONCLUSIONS: Despite comparable decreases in total and trunk fat, white women lost more IAAT and less SAAT than did black women. Waist circumference was not a suitable surrogate marker for tracking changes in the visceral fat compartment in black women.
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Dynamic changes in body weight have long been recognized as important indicators of risk for debilitating diseases. While weight loss or impaired growth can lead to muscle wastage, as well as to susceptibility to infections and organ dysfunctions, the development of excess fat predisposes to type 2 diabetes and cardiovascular diseases, with insulin resistance as a central feature of the disease entities of the metabolic syndrome. Although widely used as the phenotypic expression of adiposity in population and gene-search studies, body mass index (BMI), that is, weight/height(2) (H(2)), which was developed as an operational definition for classifying both obesity and malnutrition, has considerable limitations in delineating fat mass (FM) from fat-free mass (FFM), in particular at the individual level. After an examination of these limitations within the constraints of the BMI-FM% relationship, this paper reviews recent advances in concepts about health risks related to body composition phenotypes, which center upon (i) the partitioning of BMI into an FM index (FM/H(2)) and an FFM index (FFM/H(2)), (ii) the partitioning of FFM into organ mass and skeletal muscle mass, (iii) the anatomical partitioning of FM into hazardous fat and protective fat and (iv) the interplay between adipose tissue expandability and ectopic fat deposition within or around organs/tissues that constitute the lean body mass. These concepts about body composition phenotypes and health risks are reviewed in the light of race/ethnic variability in metabolic susceptibility to obesity and the metabolic syndrome.
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OBJECTIVES: To test the validity of a simple, rapid, field-adapted, portable hand-held impedancemeter (HHI) for the estimation of lean body mass (LBM) and percentage body fat (%BF) in African women, and to develop specific predictive equations. DESIGN: Cross-sectional observational study. SETTINGS: Dakar, the capital city of Senegal, West Africa. SUBJECTS: A total sample of 146 women volunteered. Their mean age was of 31.0 y (s.d. 9.1), weight 60.9 kg (s.d. 13.1) and BMI 22.6 kg/m(2) (s.d. 4.5). METHODS: Body composition values estimated by HHI were compared to those measured by whole body densitometry performed by air displacement plethysmography (ADP). The specific density of LBM in black subjects was taken into account for the calculation of %BF from body density. RESULTS: : Estimations from HHI showed a large bias (mean difference) of 5.6 kg LBM (P<10(-4)) and -8.8 %BF (P<10(-4)) and errors (s.d. of the bias) of 2.6 kg LBM and 3.7 %BF. In order to correct for the bias, specific predictive equations were developed. With the HHI result as a single predictor, error values were of 1.9 kg LBM and 3.7 %BF in the prediction group (n=100), and of 2.2 kg LBM and 3.6 %BF in the cross-validation group (n=46). Addition of anthropometrical predictors was not necessary. CONCLUSIONS: The HHI analyser significantly overestimated LBM and underestimated %BF in African women. After correction for the bias, the body compartments could easily be estimated in African women by using the HHI result in an appropriate prediction equation with a good precision. It remains to be seen whether a combination of arm and leg impedancemetry in order to take into account lower limbs would further improve the prediction of body composition in Africans.
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Nutrition assessment is important during chronic respiratory insufficiency to evaluate the level of malnutrition or obesity and should include body composition measurements. The appreciation of fat-free and fat reserves in patients with chronic respiratory insufficiency can aid in designing an adapted nutritional support, e.g., nutritional support in malnutrition and food restriction in obesity. The purpose of the present study was to cross-validate fat-free and fat mass obtained by various bioelectric impedance (BIA) formulas with the fat-free and fat mass measured by dual-energy X-ray absorptiometry (DXA) and determine the formulas that are best suited to predict the fat-free and fat mass for a group of patients with severe chronic respiratory insufficiency. Seventy-five patients (15 women and 60 men) with chronic obstructive and restrictive respiratory insufficiency aged 45-86 y were included in this study. Body composition was calculated according to 13 different BIA formulas for women and 12 for men and compared with DXA. Because of the variability, calculated as 2 standard deviations, of +/- 5.0 kg fat-free mass for women and +/- 6.4 kg for men for the best predictive formula, the use of the various existing BIA formulas was considered not clinically relevant. Therefore disease-specific formulas for patients with chronic respiratory insufficiency should be developed to improve the prediction of fat-free and fat mass by BIA in these patients.