Comparison of three techniques for body composition analysis in cystic fibrosis

1993 ◽  
Vol 75 (1) ◽  
pp. 162-166 ◽  
Author(s):  
L. C. Lands ◽  
C. Gordon ◽  
O. Bar-Or ◽  
C. J. Blimkie ◽  
R. M. Hanning ◽  
...  

Body composition analysis is an important component of nutritional assessment in cystic fibrosis (CF). No gold standard of measurement exists, and techniques applicable to healthy populations may be unsuitable for CF patients. We assessed lean body mass (LBM) in 12 children with CF by skinfold (SK) measurements, bioelectrical impedance analysis (BIA), and dual-photon absorptiometry (DPA) and repeated these measures in 10 subjects 6 mo later. SK and DPA measures in eight older CF patients and eight healthy controls were compared to evaluate any effect of disease on estimates of LBM by use of DPA. Good agreement between the measures was seen at baseline and 6 mo by use of concordance plots. However, the limits of agreement between measures ranged up to 19% of SK-derived LBM measures (baseline: SK and DPA, 2.63 to -3.93 kg; SK and BIA, 2.36 to -1.24 kg; BIA and DPA, 1.88 to -4.28 kg; 6 mo: SK and DPA, 2.10 to -3.58 kg; SK and BIA, 6.28 to -5.49 kg; BIA and DPA, 5.53 to -7.79 kg). The change in LBM over 6 mo did not correlate among the three measures. Only BIA change in LBM correlated with weight change (r = 0.716, P < 0.02), probably due to the inclusion of weight in the regression equations for determining LBM from impedance. The relationship between SK and DPA measures did not differ between the CF and control groups, suggesting that there was no effect of disease on the DPA measure. The results suggest that none of these methods is precise enough to follow short-term changes in the nutritional status of CF patients longitudinally.

2002 ◽  
Vol 26 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Paul R. Buzzell ◽  
Valerie M. Chamberlain ◽  
Stephen J. Pintauro

This study examined the effectiveness of a series of Web-based, multimedia tutorials on methods of human body composition analysis. Tutorials were developed around four body composition topics: hydrodensitometry (underwater weighing), dual-energy X-ray absorptiometry, bioelectrical impedance analysis, and total body electrical conductivity. Thirty-two students enrolled in the course were randomly assigned to learn the material through either the Web-based tutorials only (“Computer”), a traditional lecture format (“Lecture”), or lectures supplemented with Web-based tutorials (“Both”). All students were administered a validated pretest before randomization and an identical posttest at the completion of the course. The reliability of the test was 0.84. The mean score changes from pretest to posttest were not significantly different among the groups (65.4 ± 17.31, 78.82 ± 21.50, and 76 ± 21.22 for the Computer, Both, and Lecture groups, respectively). Additionally, a Likert-type assessment found equally positive attitudes toward all three formats. The results indicate that Web-based tutorials are as effective as the traditional lecture format for teaching these topics.


2018 ◽  
Author(s):  
Carla M Prado ◽  
Camila LP Oliveira ◽  
M Cristina Gonzalez ◽  
Steven B Heymsfield

Body composition assessment is an important tool in both clinical and research settings able to characterize the nutritional status of individuals in various physiologic and pathologic conditions. Health care professionals can use the information acquired by body composition analysis for the prevention and treatment of diseases, ultimately improving health status. Here we describe commonly used techniques to assess body composition in healthy individuals, including dual-energy x-ray absorptiometry, bioelectrical impedance analysis, air displacement plethysmography, and ultrasonography. Understanding the key underlying concept(s) of each assessment method, as well as its advantages and limitations, facilitates selection of the method of choice and the method of the compartment of interest. This review contains 5 figures, 3 tables and 52 references Key words: air displacement plethysmography, bioelectrical impedance analysis, body composition, disease, dual-energy x-ray absorptiometry, health, muscle mass, nutritional status, obesity, sarcopenia, ultrasound fat mass


2014 ◽  
Vol 44 (2) ◽  
pp. 279-286 ◽  
Author(s):  
Francisco Teixeira Andrade ◽  
Márvio Lobão Teixeira de Abreu ◽  
João Batista Lopes ◽  
Agustinho Valente de Figueiredo ◽  
Maria de Nazaré Bona Alencar Araripe ◽  
...  

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.


1988 ◽  
Vol 20 (5) ◽  
pp. 489???491 ◽  
Author(s):  
JOHN R. CATON ◽  
PAUL A. MOL?? ◽  
WILLIAM C. ADAMS ◽  
DOUGLAS S. HEUSTIS

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