Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry

AbstractStudies in animal science assessing nutrient and energy efficiency or determining nutrient requirements necessitate gathering exact measurements of body composition or body nutrient contents. Wet chemical analysis methods or standardized dissection are commonly applied, but both are destructive. Harnessing human medical imaging techniques for animal science can enable repeated measurements of individuals over time and reduce the number of individuals required for research. Among imaging techniques, dual-energy X-ray absorptiometry (DXA) is particularly promising. However, the measurements obtained with DXA do not perfectly match dissections or chemical analyses, requiring the adjustment of the DXA via calibration equations. Several calibration regressions have been published, but comparative studies are pending. Thus, it is currently not clear whether existing regression equations can be directly used to convert DXA measurements into chemical values or whether each individual DXA device will require its own calibration. Our study builds prediction equations that relate body composition to the content of single nutrients in growing entire male pigs (body weight range 20-100 kg) as determined by both DXA and chemical analyses, with R2 ranging between 0.89 for ash and 0.99 for water and crude protein. Moreover, we show that the chemical composition of the empty body can be satisfactorily determined by DXA scans of carcasses, with the prediction error rCV ranging between 4.3% for crude protein and 12.6% for ash. Finally, we compare existing prediction equations for pigs of a similar range of body weights with the equations derived from our DXA measurements and evaluate their fit with our chemical analyses data. We found that existing equations for absolute contents that were built using the same DXA beam technology predicted our data more precisely than equations based on different technologies and percentages of fat and lean mass. This indicates that the creation of generic regression equations that yield reliable estimates of body composition in pigs of different growth stages, sexes and genetic breeds could be achievable in the near future. DXA may be a promising tool for high-throughput phenotyping for genetic studies, because it efficiently measures body composition in a large number and wide array of animals.

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Dual energy X-ray absorptiometry is a valid tool for assessing in vivo body composition of broilers

Animal Production Science ◽

10.1071/an17637 ◽

2019 ◽

Vol 59 (5) ◽

pp. 993 ◽

Cited By ~ 1

Author(s):

Camila Angelica Gonçalves ◽

Nilva Kazue Sakomura ◽

Edney Pereira da Silva ◽

Silvana Martinez Baraldi Artoni ◽

Rafael Massami Suzuki ◽

...

Keyword(s):

Body Composition ◽

Crude Protein ◽

Dual Energy ◽

The Body ◽

Invasive Technique ◽

Composition Analysis ◽

Regression Equations ◽

X Ray ◽

Non Invasive

The use of non-invasive techniques to estimate body composition in animals in vivo conforms to the desire to improve the welfare of animals during research and also has the potential to advance scientific research. The purpose of the present study was to determine a predictive equation of the dual energy X-ray absorptiometry (DXA) method for broilers by comparing the measurement of body composition using DXA with that by chemical analysis. In total, 720 day-old Cobb500 broilers were distributed into a split-plot arrangement 3 (crude protein concentrations of diets) × 2 (genders) × 2 (methods of chemical body evaluation), with six replications of 20 birds each. To promote the modification of the body composition of broilers, diets varied in the crude protein concentration, which was 70%, 100% and 130% of the required. Two hundred and sixteen birds in different ages were evaluated by its bodyweight, lean, fat and ash contents. The data were submitted to ANOVA and it was demonstrated that the dietary crude protein levels applied allowed a greater variation of the body composition of the birds. Also, the results indicated that the DXA method did not predict fat mass, lean mass or bone mineral content as well as did chemical composition analysis, resulting in the need to develop regression equations for improving the in vivo prediction of these chemical components. The regression equations developed here enable the feather-free body composition of individual broilers to be directly estimated throughout growth using the DXA non-invasive technique.

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Predicting Football Players' Dual-Energy X-Ray Absorptiometry Body Composition Using Standard Anthropometric Measures

Journal of Athletic Training ◽

10.4085/1062-6050-47.3.12 ◽

2012 ◽

Vol 47 (3) ◽

pp. 257-263 ◽

Cited By ~ 19

Author(s):

Jonathan M. Oliver ◽

Brad S. Lambert ◽

Steven E. Martin ◽

John S. Green ◽

Stephen F. Crouse

Keyword(s):

Body Composition ◽

Health Risk ◽

National Collegiate Athletic Association ◽

Skinfold Thickness ◽

Dual Energy ◽

Football Players ◽

Regression Equations ◽

Anthropometric Measures ◽

X Ray ◽

Collegiate Football

Context: The recent increase in athlete size, particularly in football athletes of all levels, coupled with the increased health risk associated with obesity warrants continued monitoring of body composition from a health perspective in this population. Equations developed to predict percentage of body fat (%Fat) have been shown to be population specific and might not be accurate for football athletes. Objective: To develop multiple regression equations using standard anthropometric measurements to estimate dual-energy x-ray absorptiometry %Fat (DEXA%Fat) in collegiate football players. Design: Controlled laboratory study. Patients and Other Participants: One hundred fifty-seven National Collegiate Athletic Association Division IA football athletes (age = 20 ± 1 years, height = 185.6 ± 6.5 cm, mass = 103.1 ± 20.4 kg, DEXA%Fat = 19.5 ± 9.1%) participated. Main Outcome Measure(s): Participants had the following measures: (1) body composition testing with dual-energy x-ray absorptiometry; (2) skinfold measurements in millimeters, including chest, triceps, subscapular, midaxillary, suprailiac, abdominal (SFAB), and thigh; and (3) standard circumference measurements in centimeters, including ankle, calf, thigh, hip (AHIP), waist, umbilical (AUMB), chest, wrist, forearm, arm, and neck. Regression analysis and fit statistics were used to determine the relationship between DEXA%Fat and each skinfold thickness, sum of all skinfold measures (SFSUM), and individual circumference measures. Results: Statistical analysis resulted in the development of 3 equations to predict DEXA%Fat: model 1, (0.178 • AHIP) + (0.097 • AUMB) + (0.089 • SFSUM) − 19.641; model 2, (0.193 • AHIP) + (0.133 • AUMB) + (0.371 • SFAB) − 23.0523; and model 3, (0.132 • SFSUM) + 3.530. The R2 values were 0.94 for model 1, 0.93 for model 2, and 0.91 for model 3 (for all, P < .001). Conclusions: The equations developed provide an accurate way to assess DEXA%Fat in collegiate football players using standard anthropometric measures so athletic trainers and coaches can monitor these athletes at increased health risk due to increased size.

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Head, Neck, Trunk, and Pelvis Tissue Mass Predictions for Older Adults using Anthropometric Measures and Dual-Energy X-Ray Absorptiometry

International Journal of Kinesiology and Sports Science ◽

10.7575/aiac.ijkss.v.8n.3p.14 ◽

2020 ◽

Vol 8 (3) ◽

pp. 14

Author(s):

Charles A.J. Kahelin ◽

Nicole C. George ◽

Danielle L. Gyemi ◽

David M. Andrews

Keyword(s):

Older Adults ◽

Dual Energy ◽

Regression Equations ◽

Prediction Equations ◽

Tissue Mass ◽

Younger Adults ◽

X Ray ◽

Recreational Activities ◽

Biomechanical Models ◽

Head Neck

Background: Regression equations using anthropometric measurements to predict soft (fat mass [FM], lean mass [LM], wobbling mass [WM]) and rigid (bone mineral content [BMC]) tissue masses of the extremities and core body segments have been developed for younger adults (16-35 years), but not older adults (36-65 years). Tissue mass estimates such as these would facilitate biomechanical modeling and analyses of older adults following fall or collision-related impacts that might occur during sport and recreational activities. Purpose: The purpose of this study was to expand on the previously established tissue mass prediction equations of the head, neck, trunk, and pelvis for healthy, younger adults by generating a comparable set of equations for an older adult population. Methods: A generation sample (38 males, 38 females) was used to create head, neck, trunk, and pelvis tissue mass prediction equations via multiple linear stepwise regression. A validation sample (13 males, 12 females) was used to assess equation accuracy; actual tissue masses were acquired from manually segmented full body Dual-Energy X-ray Absorptiometry scans. Results: Adjusted R2 values for the prediction equations ranged from 0.326 to 0.949, where BMC equations showed the lowest explained variances overall. Mean relative errors between actual and predicted masses ranged from –2.6% to 6.1% for trunk LM and FM, respectively. All actual tissue masses except head BMC (R2 = 0.092) were significantly correlated to those predicted from the equations (R2 = 0.403 to 0.963). Conclusion: This research provides a simple and effective method for predicting head, neck, trunk, and pelvis tissue masses in older adults that can be incorporated into biomechanical models for analyzing sport and recreational activities. Future work with this population should aim to improve core segment BMC predictions and develop equations for the extremities.

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Validation of a Multielectrode Bioelectrical Impedance Analyzer With a Dual-Energy X-Ray Absorptiometer for the Assessment of Body Composition in Older Adults

Journal of Aging and Physical Activity ◽

10.1123/japa.2019-0211 ◽

2020 ◽

Vol 28 (4) ◽

pp. 598-604

Author(s):

Nathan F. Meier ◽

Yang Bai ◽

Chong Wang ◽

Duck-chul Lee

Keyword(s):

Older Adults ◽

Body Composition ◽

Bioelectrical Impedance ◽

Dual Energy ◽

Fat Free Mass ◽

Percentage Error ◽

Prediction Equations ◽

X Ray ◽

History Of ◽

The Mean

Changes in body composition are related to mobility, fall risk, and mortality, especially in older adults. Various devices and methods exist to measure body composition, but bioelectrical impedance analysis (BIA) has several advantages. The purpose of this study was to validate a common BIA device with a dual-energy X-ray absorptiometer (DXA) in older adults and develop prediction equations to improve the accuracy of the BIA measurements. The participants were 277 older adults (162 women and 115 men; age 73.9 ± 5.8 years) without a history of cancer and without a history of severe medical or mental conditions. Individuals fasted 12 hr before BIA and DXA measurement. The correlations between the two methods for appendicular lean mass (ALM), fat-free mass (FFM), and percentage body fat (%BF) were .86, .93, and .92, respectively, adjusting for age and sex. The mean percentage error (DXA—InBody) and mean absolute percentage error were −12% and 13% for ALM, −13% and 13% for FFM, and 16% and 17% for %BF. The prediction equations estimated ALM, FFM, and %BF; sex was coded as 1 for male and 0 for female: Although highly correlated, BIA overestimated FFM, and ALM and underestimated %BF compared with DXA. An application of prediction equations eliminated the mean error and reduced the range of individual error across the sample. Prediction equations may improve BIA accuracy sufficiently to substitute for DXA in some cases.

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Head, Neck, Trunk, and Pelvis Tissue Mass Predictions for Young Adults Using Anthropometric Measures and Dual-Energy X-Ray Absorptiometry

Journal of Applied Biomechanics ◽

10.1123/jab.2016-0228 ◽

2017 ◽

Vol 33 (5) ◽

pp. 366-372

Author(s):

Danielle L. Gyemi ◽

Charles Kahelin ◽

Nicole C. George ◽

David M. Andrews

Keyword(s):

Young Adults ◽

Head And Neck ◽

Dual Energy ◽

Regression Equations ◽

Prediction Equations ◽

Anthropometric Measures ◽

Tissue Mass ◽

X Ray ◽

Head Neck

Accurate prediction of wobbling mass (WM), fat mass (FM), lean mass (LM), and bone mineral content (BMC) of living people using regression equations developed from anthropometric measures (lengths, circumferences, breadths, skinfolds) has previously been reported, but only for the extremities. Multiple linear stepwise regression was used to generate comparable equations for the head, neck, trunk, and pelvis of young adults (38 males, 38 females). Equations were validated using actual tissue masses from an independent sample of 13 males and 13 females by manually segmenting full-body dual-energy x-ray absorptiometry scans. Prediction equations exhibited adjusted R2 values ranging from .249 to .940, with more explained variance for LM and WM than BMC and FM, especially for the head and neck. Mean relative errors between predicted and actual tissue masses ranged from −11.07% (trunk FM) to 7.61% (neck FM). Actual and predicted tissue masses from all equations were significantly correlated (R2 = .329 to .937), except head BMC (R2 = .046). These results show promise for obtaining in-vivo head, neck, trunk, and pelvis tissue mass estimates in young adults. Further research is needed to improve head and neck FM and BMC predictions and develop tissue mass prediction equations for older populations.

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Accuracy of predicting chemical body composition of growing pigs using dual-energy X-ray absorptiometry

animal ◽

10.1016/j.animal.2021.100307 ◽

2021 ◽

Vol 15 (8) ◽

pp. 100307

Author(s):

C. Kasper ◽

P. Schlegel ◽

I. Ruiz-Ascacibar ◽

P. Stoll ◽

G. Bee

Keyword(s):

Body Composition ◽

Dual Energy ◽

Growing Pigs ◽

X Ray

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AB0267 BODY COMPOSITION IN PATIENTS WITH RHEUMATOID ARTHRITIS

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.2318 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1432.2-1432

Author(s):

N. Toroptsova ◽

O. Dobrovolskaya ◽

N. Demin ◽

L. Shornikova

Keyword(s):

Rheumatoid Arthritis ◽

Body Composition ◽

Muscle Mass ◽

Dual Energy ◽

X Ray ◽

T Score ◽

Osteosarcopenic Obesity ◽

The Mean ◽

Total Fat ◽

Appendicular Muscle Mass

Background:Rheumatoid arthritis (RA) is a complex inflammatory disease that modifies body composition. Using the dual-energy x-ray absorptiometry (DXA) in RA patients could be a method for body composition changes detection.Objectives:To study the body composition using DXA in patients with RA.Methods:The study involved 79 women with RA, median age 60 [55; 65] years. The bone mineral density (BMD) was measured by dual-energy x-ray absorptiometry using «Discovery A» (Hologic, USA). Assessment of body composition was carried out, using the program «Whole body». Sarcopenia (SP) was diagnosed as a decrease in appendicular mass index (AMI) <6.0 kg/m2. Osteoporosis (OP) was diagnosed as a decrease in T-score <-2.5 SD. Osteosarcopenia was determined when T-score was <-1.0 SD, AMI was <6.0 kg/m2, osteosarcopenic obesity - T-score was <-1.0 SD, AMI was <6.0 kg/m2and total fat was >35%.Results:The mean duration of RA was 9 [3; 11] years. The mean body mass index (BMI) was 27.6±4.8 kg/m2. Disease activity score in 28 joints-erythrocyte sedimentation rate was 4.5±1.3 points for the group. 39 (49.3%) patients used oral glucocorticoids continuously. Appendicular muscle mass and AMI were on average 17.8±3.0 kg and 6.8±1.0 kg/m2, respectively. AMI <6 kg/m2was detected in 20 (25.3%) patients. 56 (70.9%) women with RA had total fat > 35%, while only 22 (27.8%) of women with RA had obesity according to BMI (BMI >30 kg/m2). Isolated OP was found in 13 (16.5%), osteosarcopenia in 7 (8.9%) and osteosarcopenic obesity in 13 (16.5%) patients RA. No cases with isolated sarcopenia or sarcopenic obesity were detected. Only 3 (3.8%) patients did not have appendicular muscle mass, AMI and BMD decrease and overfat or obesity.Conclusion:About 97% women with RA had abnormal body composition phenotype: 16,5% - OP, 8.9% -osteosarcopenia, 16,5% - osteosarcopenic obesity and 54,4% - overfat.Disclosure of Interests:None declared

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