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Chang CY, Lenchik L, Blankemeier L, Chaudhari AS, Boutin RD. Biomarkers of Body Composition. Semin Musculoskelet Radiol 2024; 28:78-91. [PMID: 38330972 DOI: 10.1055/s-0043-1776430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
The importance and impact of imaging biomarkers has been increasing over the past few decades. We review the relevant clinical and imaging terminology needed to understand the clinical and research applications of body composition. Imaging biomarkers of bone, muscle, and fat tissues obtained with dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging, and ultrasonography are described.
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Affiliation(s)
- Connie Y Chang
- Division of Musculoskeletal Imaging and Intervention, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Leon Lenchik
- Department of Radiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Louis Blankemeier
- Department of Electrical Engineering, Stanford University, Stanford, California
| | - Akshay S Chaudhari
- Department of Radiology and of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
| | - Robert D Boutin
- Department of Radiology, Stanford University School of Medicine, Stanford, California
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Bennett JP, Cataldi D, Liu YE, Kelly NN, Quon BK, Schoeller DA, Kelly T, Heymsfield SB, Shepherd JA. Development and validation of a rapid multicompartment body composition model using 3-dimensional optical imaging and bioelectrical impedance analysis. Clin Nutr 2024; 43:346-356. [PMID: 38142479 DOI: 10.1016/j.clnu.2023.12.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 11/21/2023] [Accepted: 12/11/2023] [Indexed: 12/26/2023]
Abstract
BACKGROUND & AIMS The multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). METHODS Samples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. RESULTS 67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95 % limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95 % LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. CONCLUSIONS Body composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.
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Affiliation(s)
- Jonathan P Bennett
- Graduate Program in Human Nutrition, University of Hawai'i at Manoa, Agricultural Science Building, 1955 East-West Rd, Honolulu, HI, 96822, USA; Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Devon Cataldi
- Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Yong En Liu
- Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Nisa N Kelly
- Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Brandon K Quon
- Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA
| | - Dale A Schoeller
- Department of Nutritional Sciences, University of Wisconsin-Madison, 1415 Linden Drive, Madison, WI, 53706, USA
| | - Thomas Kelly
- Hologic Inc, 250 Campus Drive, Marlborough, MA, 01752, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, Louisiana State University, 6400 Perkins Rd, Baton Rouge, LA, 70808, USA
| | - John A Shepherd
- Graduate Program in Human Nutrition, University of Hawai'i at Manoa, Agricultural Science Building, 1955 East-West Rd, Honolulu, HI, 96822, USA; Department of Epidemiology, University of Hawai'i Cancer Center, 701 Ilalo St, Honolulu, HI, 96813, USA.
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Cataldi D, Bennett JP, Wong MC, Quon BK, Liu YE, Kelly NN, Kelly T, Schoeller DA, Heymsfield SB, Shepherd JA. Accuracy and precision of multiple body composition methods and associations with muscle strength in athletes of varying hydration: The Da Kine Study. Clin Nutr 2024; 43:284-294. [PMID: 38104490 DOI: 10.1016/j.clnu.2023.11.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Athletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels. METHODS The Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry. RESULTS In total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63-73 %) and females (58-78 %). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin's Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC <0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0 %). Increasing quartiles (significant p < 0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status. CONCLUSION The criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations. SUMMARY BOX This study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.
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Affiliation(s)
- Devon Cataldi
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Jonathan P Bennett
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Michael C Wong
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Brandon K Quon
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Yong En Liu
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Nisa N Kelly
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA
| | - Thomas Kelly
- Hologic Inc, 250 Campus Dr, Marlborough, MA 01752, USA
| | - Dale A Schoeller
- Isotope Ratio Core Biotech Center and Nutritional Sciences, Henry Mall Madison, WI 53706, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA, 7080, USA
| | - John A Shepherd
- Department of Epidemiology, University of Hawaii Cancer Center, 701 Ilalo Street, Honolulu, HI, 96813, USA.
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Bioimpedance for assessing adiposity: The importance of comparisons. Am J Clin Nutr 2023; 117:639-640. [PMID: 36872024 DOI: 10.1016/j.ajcnut.2022.12.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 12/10/2023] [Indexed: 03/06/2023] Open
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Bennett JP, Liu YE, Kelly NN, Quon BK, Wong MC, McCarthy C, Heymsfield SB, Shepherd JA. Reply to Y Lu et al. Am J Clin Nutr 2023; 117:641-642. [PMID: 36872025 DOI: 10.1016/j.ajcnut.2023.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 01/05/2023] [Indexed: 03/06/2023] Open
Affiliation(s)
- Jonathan P Bennett
- From the Graduate Program in Human Nutrition, University of Hawai'i Manoa, Honolulu, HI, USA; The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA.
| | - Yong En Liu
- The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Nisa N Kelly
- The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Brandon K Quon
- The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Michael C Wong
- From the Graduate Program in Human Nutrition, University of Hawai'i Manoa, Honolulu, HI, USA; The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Cassidy McCarthy
- The Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA
| | - Steven B Heymsfield
- The Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA, USA
| | - John A Shepherd
- From the Graduate Program in Human Nutrition, University of Hawai'i Manoa, Honolulu, HI, USA; The Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
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Brandner CF, Tinsley GM, Graybeal AJ. Smartwatch-based bioimpedance analysis for body composition estimation: precision and agreement with a 4-compartment model. Appl Physiol Nutr Metab 2023; 48:172-182. [PMID: 36462216 DOI: 10.1139/apnm-2022-0301] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
Given that the prevalence of smartwatches has allowed them to become a hallmark in health monitoring, they are primed to provide accessible body composition estimations. The purpose of this study was to evaluate the precision and agreement of smartwatch-based bioimpedance analysis (SW-BIA) and multifrequency bioimpedance analysis (MFBIA) against a 4-compartment (4C) model criterion. A total of 186 participants (114 females) underwent body composition assessments necessary for a 4C model and SW-BIA and MFBIA. Values of total body water (TBW) from each device were compared with those obtained from bioimpedance spectroscopy. Precision was adequate though slightly lower for the smartwatch compared with other methods. No device demonstrated equivalence with the 4C model. Specifically, the SW-BIA overestimated and MFBIA underestimated body fat. MFBIA, but not SW-BIA, demonstrated equivalence for TBW. Overall error was higher for males using the smartwatch compared with females. While these findings do not invalidate the use of smartwatch-based estimates, clinicians should consider that there may be large errors relative to clinical measures. If this wearable device is intended to be used to monitor body composition change over time, these findings demonstrate the need for future research to evaluate its accuracy during follow-up testing.
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Affiliation(s)
- Caleb F Brandner
- School of Kinesiology & Nutrition, College of Education and Human Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA
| | - Grant M Tinsley
- Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX 79409, USA
| | - Austin J Graybeal
- School of Kinesiology & Nutrition, College of Education and Human Sciences, University of Southern Mississippi, Hattiesburg, MS 39406, USA
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