scholarly journals Body Composition Assessment of Nutritional Status using Near‐Infrared Spectroscopy, Bioelectrical Impedance and Air Displacement Plethysmograph in Young Athletes

2015 ◽  
Vol 29 (S1) ◽  
Author(s):  
Alma MENDOZA ◽  
MARIA AVILES ◽  
CLAUDIA SANCHEZ
Keyword(s):  
Body Composition ◽  
Infrared Spectroscopy ◽  
Nutritional Status ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Bioelectrical Impedance ◽  
Young Athletes ◽  
Body Composition Assessment

COMPARISON OF NEAR-INFRARED SPECTROSCOPY AND BIOELECTRICAL IMPEDANCE ANALYSIS FOR THE ASSESSMENT OF BODY COMPOSITION IN THE FRAIL ELDERLY

2014 ◽  
pp. 1-5
Author(s):  
T. KAMO ◽  
H. ISHII ◽  
D. TAKAHASHI ◽  
K. IWAGAYA ◽  
T. ISHIDA ◽  
...  
Keyword(s):  
Body Composition ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Frail Elderly ◽  
Bioelectrical Impedance Analysis ◽  
Near Infrared ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Community Dwelling ◽  
Composition Analysis

Background: Body composition is an important component of health related fitness. Near-infrared spectroscopy (NIRS) is a non-invasive, simple and rapid method of assessing body fat percentage. However, it is unknown whether NIRS can accurately estimate FFM in community-dwelling frail elderly. Objectives: This study aimed to compare NIRS with bioelectrical impedance analysis (BIA) in FFM measurement. Design: Cross-sectional study. Setting: Shizuoka, Japan. Participants: The study population comprised 53 community-dwelling frail elderly (15 men, 38 women; mean age 84.8±6.4 years; body mass index 19.7±3.5 kg/m2). Measurement: FFM and percentage fat mass (%FM) were estimated using a NIRS device at two sites (biceps and calf) and compared to body composition measured by BIA. Simple linear regression and Bland–Altman analyses were used to determine agreement between the methods. Results: FFM determined by BIA highly correlated with that determined by NIRS at both the biceps and calf (r=0.92 for both; p<0.001). The correlation coefficients for %FM estimated by NIRS were slightly lower (r=0.70 for biceps; r=0.66 for calf). In NIRS assessments, systematic biases were found for %FM but not for FFM. Conclusion: NIRS has significant potential for body composition analysis. Further comparative and longitudinal studies need to be conducted using an agreed reference analysis method to find a simple and more suitable method that can be applied among the community-dwelling frail elderly.

Techniques For Assessment Of Body Composition In Health

2018 ◽  
Author(s):  
Carla M Prado ◽  
Camila LP Oliveira ◽  
M Cristina Gonzalez ◽  
Steven B Heymsfield
Keyword(s):  
Body Composition ◽  
Nutritional Status ◽  
Bioelectrical Impedance Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Dual Energy ◽  
Composition Analysis ◽  
Body Composition Assessment ◽  
Air Displacement Plethysmography ◽  
X Ray

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

Near-Infrared Spectroscopy to Monitor Nutritional Status of Neonates: A Review

2020 ◽  
Vol 13 ◽  
pp. 280-291
Author(s):  
Alexander P. Miller ◽  
Fatin Hamimi Mustafa ◽  
Peter W. Jones ◽  
Heather E. Jeffery ◽  
Angela E. Carberry ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Nutritional Status ◽  
Near Infrared Spectroscopy ◽  
Near Infrared

Near-infrared spectroscopy and X-ray fluorescence data fusion for olive leaf analysis and crop nutritional status determination

Talanta ◽  
2018 ◽  
Vol 188 ◽  
pp. 676-684 ◽  
Author(s):  
F. Comino ◽  
M.J. Ayora-Cañada ◽  
V. Aranda ◽  
A. Díaz ◽  
A. Domínguez-Vidal
Keyword(s):  
Infrared Spectroscopy ◽  
Nutritional Status ◽  
Data Fusion ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Olive Leaf ◽  
X Ray ◽  
Leaf Analysis

Comparison of Four Methods to Assess Body Composition in Black and White Athletes

1992 ◽  
Vol 2 (1) ◽  
pp. 60-74 ◽  
Author(s):  
Tibor Hortobágyi ◽  
Richard G. Israel ◽  
Joseph A. Houmard ◽  
Kevin F. O'Brien ◽  
Robert A. Johns ◽  
...  
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
Near Infrared ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
American Football ◽  
Percent Body Fat ◽  
Body Composition Assessment ◽  
Black And White ◽  
Hydrostatic Weighing

Four methods of assessing body composition were compared in 55 black and 35 white, Division 1, American football players. Percent body fat (%BF) was estimated with hydrostatic weighing at residual volume, corrected for race; seven-site skinfolds (7 SF), corrected for race; bioelectrical impedance analysis (BIA); and near-infrared spectrophotometry (NIR). Percent body fat with HW in blacks (mean = 14.7%) and whites (19.7%) did not differ(P> .05) from %>BF with 7 SF (blacks, 14.7%; whites, 19.0%). In relation to HW, BIA significantly(P <.05) overpredicted (blacks: 20.1%,SEE =3.2%; whites; 22.3%,SEE =4.3%) and NiR underpredicted %BF (blacks; 12.6%,SEE= 3.9%; whites; 17.7%,SEE= 3.6%). The contribution of BIA variables (resistance, phase angle, conductance) and NIR optical density to predict %BF was trivial compared to body mass index. It appears that race may not substantially influence %BF prediction by NIR and BIA. It was concluded that when considering the cost and expertise required with NIR and BIA, SF measurements appear to be a superior alternative for rapid and accurate body composition assessment of athletes, independent of race.

scholarly journals Muscle blood flow as an indicator of anaerobic threshold in young athletes – A near infrared spectroscopy study

2017 ◽  
Vol 9 (3) ◽  
pp. 63-75
Author(s):  
Maciej Chroboczek ◽  
Mgdalena Jakubowska ◽  
Sylwester Kujach ◽  
Marcin Łuszczak ◽  
Radosław Laskowski
Keyword(s):  
Blood Flow ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Anaerobic Threshold ◽  
Near Infrared ◽  
Muscle Blood Flow ◽  
Spectroscopy Study ◽  
Young Athletes

scholarly journals Rapid Differentiation of Unfrozen and Frozen-Thawed Tuna with Non-Destructive Methods and Classification Models: Bioelectrical Impedance Analysis (BIA), Near-Infrared Spectroscopy (NIR) and Time Domain Reflectometry (TDR)

Foods ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 55
Author(s):  
Sonia Nieto-Ortega ◽  
Ángela Melado-Herreros ◽  
Giuseppe Foti ◽  
Idoia Olabarrieta ◽  
Graciela Ramilo-Fernández ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Near Infrared Spectroscopy ◽  
Time Domain ◽  
Bioelectrical Impedance Analysis ◽  
Near Infrared ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Time Domain Reflectometry ◽  
Non Destructive

The performances of three non-destructive sensors, based on different principles, bioelectrical impedance analysis (BIA), near-infrared spectroscopy (NIR) and time domain reflectometry (TDR), were studied to discriminate between unfrozen and frozen-thawed fish. Bigeye tuna (Thunnus obesus) was selected as a model to evaluate these technologies. The addition of water and additives is usual in the fish industry, thus, in order to have a wide range of possible commercial conditions, some samples were injected with different water solutions (based on different concentrations of salt, polyphosphates and a protein hydrolysate solution). Three different models, based on partial least squares discriminant analysis (PLS-DA), were developed for each technology. This is a linear classification method that combines the properties of partial least squares (PLS) regression with the classification power of a discriminant technique. The results obtained in the evaluation of the test set were satisfactory for all the sensors, giving NIR the best performance (accuracy = 0.91, error rate = 0.10). Nevertheless, the classification accomplished with BIA and TDR data resulted also satisfactory and almost equally as good, with accuracies of 0.88 and 0.86 and error rates of 0.14 and 0.15, respectively. This work opens new possibilities to discriminate between unfrozen and frozen-thawed fish samples with different non-destructive alternatives, regardless of whether or not they have added water.

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