|
1
|
Heymsfield SB. Advances in body composition: a 100-year journey. Int J Obes (Lond) 2025; 49:177-181. [PMID: 38643327 PMCID: PMC11805704 DOI: 10.1038/s41366-024-01511-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 02/28/2024] [Accepted: 03/05/2024] [Indexed: 04/22/2024]
Abstract
Knowledge of human body composition at the dawn of the twentieth century was based largely on cadaver studies and chemical analyses of isolated organs and tissues. Matters soon changed by the nineteen twenties when the Czech anthropologist Jindřich Matiegka introduced an influential new anthropometric method of fractionating body mass into subcutaneous adipose tissue and other major body components. Today, one century later, investigators can not only quantify every major body component in vivo at the atomic, molecular, cellular, tissue-organ, and whole-body organizational levels, but go far beyond to organ and tissue-specific composition and metabolite estimates. These advances are leading to an improved understanding of adiposity structure-function relations, discovery of new obesity phenotypes, and a mechanistic basis of some weight-related pathophysiological processes and adverse clinical outcomes. What factors over the past one hundred years combined to generate these profound new body composition measurement capabilities in living humans? This perspective tracks the origins of these scientific innovations with the aim of providing insights on current methodology gaps and future research needs.
Collapse
Affiliation(s)
- Steven B Heymsfield
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, USA.
| |
Collapse
|
|
2
|
Masset KVDSB, Silva AM, Ferrari G, Cabral BGDAT, Dantas PMS, Da Costa RF. Development and cross-validation of predictive equations for fat-free mass estimation by bioelectrical impedance analysis in Brazilian subjects with overweight and obesity. Front Nutr 2025; 12:1499752. [PMID: 39902311 PMCID: PMC11788142 DOI: 10.3389/fnut.2025.1499752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Accepted: 01/06/2025] [Indexed: 02/05/2025] Open
Abstract
Introduction Obesity is a public health problem worldwide, and body composition assessment is a very important diagnostic tool. Bioelectrical Impedance Analysis (BIA) is a fast, non-invasive, relatively low-cost, and user-friendly technique; however, to obtain greater validity of the estimates, the predictive equations used must be population specific. Thus, the objectives of this study were: (1) to test the validity of four BIA equations used for fat-free mass (FFM) estimation and one model for fat mass (FM) estimation in adults with overweight or obesity; (2) develop and cross-validate new equations to estimate FFM to adults with overweight or obesity, and specific for those with obesity. Methods The non-probabilistic sample included 269 individuals, 53.2% with overweight and 46.8% with obesity, aged 18-79 years, randomly divided into two groups: development (n = 178) and cross-validation (n = 91), stratified by sex and classification as overweight or obese. The criterion technique was dual-energy-x-ray absorptiometry (DXA), whereas a tetrapolar single-frequency BIA equipment was used as the alternative method. Paired t-test, multiple regression, concordance correlation coefficient, and Bland-Altman analysis were used. Results Most existing equations were not valid and new equations were derived: (1) for individuals with overweight or obesity: CCC = 0.982; r2 = 0.95; standard error of estimate (SEE) = 2.50 kg; limits of agreement (LOA) = -5.0 to 4.8; and (2) specific for individuals with obesity: CCC = 0.968; r2 = 0.94; SEE = 2.53 kg; LOA = -5.3 to 5.2. No FFM differences were observed between the new models and the reference method (p > 0.05). Conclusion The new proposed models provide valid options to estimate FFM in an adult population with overweight/obesity.
Collapse
Affiliation(s)
| | - Analiza M. Silva
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
- Department of Movement Sciences and Sports Training, School of Sport Sciences, The University of Jordan, Amman, Jordan
| | - Gerson Ferrari
- Escuela de Ciencias de la Actividad Física, el Deporte y la Salud, Universidad de Santiago de Chile (USACH), Santiago, Chile
- Faculty of Health Sciences, Universidad Autónoma de Chile, Providencia, Chile
| | | | - Paulo Moreira Silva Dantas
- Department of Physical Education, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | | |
Collapse
|
|
3
|
Hatamoto Y, Tanoue Y, Tagawa R, Yasukata J, Shiose K, Kose Y, Watanabe D, Tanaka S, Chen KY, Ebine N, Ueda K, Uehara Y, Higaki Y, Sanbongi C, Kawanaka K. Greater energy surplus promotes body protein accretion in healthy young men: A randomized clinical trial. Clin Nutr 2024; 43:48-60. [PMID: 39423761 DOI: 10.1016/j.clnu.2024.09.035] [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: 02/20/2024] [Revised: 09/01/2024] [Accepted: 09/20/2024] [Indexed: 10/21/2024]
Abstract
BACKGROUND & AIMS Caloric overfeeding combined with adequate protein intake increases not only body fat mass but also fat-free mass. However, it remains unclear whether the increase in fat-free mass due to overfeeding is associated with an increase in total body protein mass. We evaluated the hypothesis that overfeeding would promote an increase in total body protein mass. METHODS In our randomized controlled trial, 23 healthy young men were fed a diet equivalent to their energy requirements with a +10 % energy surplus from protein alone or a +40 % energy surplus (+10 % from protein, +30 % from carbohydrate) for 6 weeks. We estimated total body protein mass by a four-compartment model using dual-energy X-ray absorptiometry, deuterium dilution, and hydrostatic underwater weighing. RESULTS The 40 % energy surplus over 6 weeks significantly increased body protein mass compared to baseline by 3.7 % (0.44 kg; 95 % confidence interval [CI], 0.21-0.67 kg; P = 0.003); however, the 10 % energy surplus did not result in a significant change (0.00 kg; 95 % CI, -0.38-0.39 kg; P = 0.980). A significant interaction between intervention duration (time) and energy surplus (group) was observed for total body protein mass (P = 0.035, linear mixed-effects model), with a trend toward a significant difference in total body protein mass gain between groups (P = 0.059, Wilcoxon rank sum test). The increase in body protein mass due to the energy surplus was correlated with an increase in fat mass (r = 0.820, p = 0.002). CONCLUSIONS A higher energy intake was found to promote an increase in body protein mass in healthy men consuming excess protein, suggesting the importance of energy surplus in body protein accumulation. This effect of energy surplus may be related to factors such as increased body fat mass and the associated secretion of adipokines. TRIAL REGISTRATION The trial was registered with the University Hospital Medical Information Network Clinical Trial Registry as UMIN000034158.
Collapse
Affiliation(s)
- Yoichi Hatamoto
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan
| | - Yukiya Tanoue
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Ritsumeikan-Global Innovation Research Organization, Ritsumeikan University, Shiga, Japan
| | - Ryoichi Tagawa
- Wellness Science Labs, Meiji Holdings Co Ltd, Tokyo, Japan; School of Sports Sciences, Waseda University, Saitama, Japan
| | - Jun Yasukata
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Institute for Comprehensive Education, Kagoshima University, Kagoshima, Japan
| | - Keisuke Shiose
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Faculty of Education, University of Miyazaki, Miyazaki, Japan
| | - Yujiro Kose
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; National Institute of Fitness and Sports in Kanoya, Kagoshima, Japan
| | - Daiki Watanabe
- School of Sports Sciences, Waseda University, Saitama, Japan; Department of Physical Activity Research, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan
| | - Shigeho Tanaka
- Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, Japan; Faculty of Nutrition, Kagawa Nutrition University, Saitama, Japan; Institute of Nutrition Sciences, Kagawa Nutrition University, Saitama, Japan
| | - Kong Y Chen
- Diabetes, Endocrinology, and Obesity Branch, Intramural Research Program, National Institute of Diabetes and Digestive and Kidney Diseases, The National Institutes of Health, Bethesda, MD, USA
| | - Naoyuki Ebine
- Faculty of Health and Sports Science, Doshisha University, Kyoto, Japan
| | - Keisuke Ueda
- Nutritionals Development Dept. Global Nutritional Business Div. Meiji Co., Ltd. Tokyo Japan, Japan
| | - Yoshinari Uehara
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan
| | - Yasuki Higaki
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan
| | - Chiaki Sanbongi
- Nutrition and Food Function Group Health Science Research Unit, R&D Division, Meiji Co, Ltd, Tokyo, Japan
| | - Kentaro Kawanaka
- Institute for Physical Activity, Fukuoka University, Fukuoka, Japan; Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan.
| |
Collapse
|
|
4
|
Heymsfield SB, Brown J, Ramirez S, Prado CM, Tinsley GM, Gonzalez MC. Are Lean Body Mass and Fat-Free Mass the Same or Different Body Components? A Critical Perspective. Adv Nutr 2024; 15:100335. [PMID: 39510253 PMCID: PMC11625996 DOI: 10.1016/j.advnut.2024.100335] [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: 07/24/2024] [Revised: 09/28/2024] [Accepted: 10/30/2024] [Indexed: 11/15/2024] Open
Abstract
The 2-component molecular-level model dividing body mass into fat and fat-free mass (FFM) is a cornerstone of contemporary body composition research across multiple disciplines. Confusion prevails, however, as the term lean body mass (LBM) is frequently used interchangeably with FFM in scientific discourse. Are LBM and FFM the same or different body components? Captain Albert R. Behnke originated the LBM concept in 1942 and he argued that his "physiological" LBM component included "essential" fat or structural lipids whereas FFM is a chemical entity "free" of fat. Classical experimental animal and human studies conducted during Behnke's era laid the foundation for the widely used body density and total body water 2-component molecular-level body composition models. Refined body composition models, organization of lipids into structural and functional groupings, and lipid extraction methods all have advanced since Behnke's era. Our review provides an in-depth analysis of these developments with the aim of clarifying distinctions between the chemical composition of LBM and FFM. Our retrospective analysis reveals that FFM, derived experimentally as the difference between body weight and extracted neutral or nonpolar lipids (mainly triglycerides), includes polar or structural lipids (that is, Behnke's "essential" fat). Accordingly, LBM as originally proposed by Behnke has the same chemical composition as FFM, thus answering a longstanding ambiguity in the body composition literature. Bringing body composition science into the modern era mandates the use of the chemically correct term FFM with the elimination of the duplicative term LBM that today has value primarily in a historical context. Avoiding the use of the term LBM additionally limits confusion surrounding similar widely used body composition terms such as lean mass, lean soft tissue mass, and lean muscle mass.
Collapse
Affiliation(s)
- Steven B Heymsfield
- Metabolism-Body Composition Core Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States.
| | - Jasmine Brown
- Metabolism-Body Composition Core Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - Sophia Ramirez
- Metabolism-Body Composition Core Laboratory, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA, United States
| | - Carla M Prado
- Department of Agricultural, Food & Nutritional Science, Human Nutrition Research Unit, University of Alberta, Edmonton, AB, Canada
| | - Grant M Tinsley
- Department of Kinesiology and Sport Management, Texas Tech University, Lubbock, TX, United States
| | | |
Collapse
|
|
5
|
Florez CM, Rodriguez C, Siedler MR, Tinoco E, Tinsley GM. Body composition estimation from mobile phone three-dimensional imaging: evaluation of the USA army one-site method. Br J Nutr 2024; 132:1-9. [PMID: 39411840 PMCID: PMC11617106 DOI: 10.1017/s0007114524002216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 07/16/2024] [Accepted: 09/10/2024] [Indexed: 12/06/2024]
Abstract
Within the USA military, monitoring body composition is an essential component of predicting physical performance and establishing soldier readiness. The purpose of this study was to explore mobile phone three-dimensional optical imaging (3DO), a user-friendly technology capable of rapidly obtaining reliable anthropometric measurements and to determine the validity of the new Army one-site body fat equations using 3DO-derived abdominal circumference. Ninety-six participants (51 F, 45 M; age: 23·7 ± 6·5 years; BMI: 24·7 ± 4·1 kg/m2) were assessed using 3DO, dual-energy X-ray absorptiometry (DXA) and a 4-compartment model (4C). The validity of the Army equations using 3DO abdominal circumference was compared with 4C and DXA estimates. Compared with the 4C model, the Army equation overestimated BF% and fat mass (FM) by 1·3 ± 4·8 % and 0·9 ± 3·4 kg, respectively, while fat-free mass (FFM) was underestimated by 0·9 ± 3·4 kg (P < 0·01 for each). Values from DXA and Army equation were similar for BF%, FM and FFM (constant errors between -0·1 and 0·1 units; P ≥ 0·82 for each). In both comparisons, notable proportional bias was observed with slope coefficients of -0·08 to -0·43. Additionally, limits of agreement were 9·5-10·2 % for BF% and 6·8-7·8 kg for FM and FFM. Overall, while group-level performance of the one-site Army equation was acceptable, it exhibited notable proportional bias when compared with laboratory criterion methods and wide limits of agreement, indicating potential concerns when applied to individuals. 3DO may provide opportunities for the development of more advanced, automated digital anthropometric body fat estimation in military settings.
Collapse
Affiliation(s)
- Christine M. Florez
- Energy Balance & Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock79409, TX, USA
| | - Christian Rodriguez
- Energy Balance & Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock79409, TX, USA
| | - Madelin R. Siedler
- Energy Balance & Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock79409, TX, USA
| | - Ethan Tinoco
- Energy Balance & Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock79409, TX, USA
| | - Grant M. Tinsley
- Energy Balance & Body Composition Laboratory, Department of Kinesiology and Sport Management, Texas Tech University, Lubbock79409, TX, USA
| |
Collapse
|
|
6
|
Seo JW, Lee S, Yim MH. Machine Learning Approach for Predicting Hypertension Based on Body Composition in South Korean Adults. Bioengineering (Basel) 2024; 11:921. [PMID: 39329663 PMCID: PMC11428396 DOI: 10.3390/bioengineering11090921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2024] [Revised: 08/28/2024] [Accepted: 09/12/2024] [Indexed: 09/28/2024] Open
Abstract
(1) Background: Various machine learning techniques were used to predict hypertension in Korean adults aged 20 and above, using a range of body composition indicators. Muscle and fat components of body composition are closely related to hypertension. The aim was to identify which body composition indicators are significant predictors of hypertension for each gender; (2) Methods: A model was developed to classify hypertension using six different machine learning techniques, utilizing age, BMI, and body composition indicators such as body fat mass, lean mass, and body water of 2906 Korean men and women; (3) Results: The elastic-net technique demonstrated the highest classification accuracy. In the hypertension prediction model, the most important variables for men were age, skeletal muscle mass (SMM), and body fat mass (BFM), in that order. For women, the significant variables were age and BFM. However, there was no difference between soft lean mass and SMM; (4) Conclusions: Hypertension affects not only BFM but also SMM in men, whereas in women, BFM has a stronger effect than SMM.
Collapse
Affiliation(s)
- Jeong-Woo Seo
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34504, Republic of Korea;
| | - Sanghun Lee
- KM Data Division, Korea Institute of Oriental Medicine, Daejeon 34504, Republic of Korea;
| | - Mi Hong Yim
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34504, Republic of Korea;
| |
Collapse
|
|
7
|
Silva AM, Campa F, Sardinha LB. The usefulness of total body protein mass models for adolescent athletes. Front Nutr 2024; 11:1439208. [PMID: 39040929 PMCID: PMC11262245 DOI: 10.3389/fnut.2024.1439208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 06/24/2024] [Indexed: 07/24/2024] Open
Abstract
The present study aimed to assess the utility of a less laborious technique for estimating total body protein (TBPro) in young athletes, using a multicomponent model as the criterion method. A total of 88 (49 boys and 39 girls) adolescent athletes (age: 15.2 ± 1.5 years; body mass index: 21.2 ± 2.7 kg/m2) participated. A 6-compartment model was used as the reference method (TBProReference) involving air displacement plethysmography for body volume, dual-energy X-ray absorptiometry (DXA) for bone mineral content, and deuterium dilution for total body water (TBW). Alternatively, DXA TBPro models were used as TBPro = lean-soft mass (LSM) - HFFFM × fat-free mass (FFM) - Ms. - G, where LSM and FFM were assessed using DXA, HFFFM is the hydration fraction of the FFM using measured TBW or assumed TBW (adult fraction of 0.732; Lohman's constants or mean observed HFFFM), Ms. is soft tissue minerals (Ms = 0.0129 × HFFFM × FFM), and G is glycogen calculated as 0.044 × (LSM - HFFFM × FFM - Ms). The maturation level was determined by self-assessment. TBPro obtained from DXA using the assumed HFFFM explained 73% to 77% of the variance compared to TBProReference. Meanwhile, using the mean values of measured HFFFM, the DXA model explained 53 and 36% for boys and girls, respectively. Larger bias (8.6% for boys and 25.8% for girls) and limits of agreement were found for the DXA model using measured HFFFM (boys for 66.9% and girls for 70%) compared to an assumed HFFFM (bias ranged from 1.5% to 22.5% and limits of agreement ranged from 31.3% to 35.3%). Less complex and demanding TBPro DXA models with the assumed HFFFM are valid alternatives for assessing this relevant FFM component in groups of adolescent athletes but are less accurate for individual results. Though future studies should be conducted to test the usefulness of these models in longitudinal and experimental designs, their potential to provide an estimation of protein mass after exercise and diet interventions in young athletes is anticipated.
Collapse
Affiliation(s)
- Analiza M. Silva
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | - Francesco Campa
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| | - Luís B. Sardinha
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| |
Collapse
|
|
8
|
Campa F, Coratella G, Cerullo G, Noriega Z, Francisco R, Charrier D, Irurtia A, Lukaski H, Silva AM, Paoli A. High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review. J Transl Med 2024; 22:515. [PMID: 38812005 PMCID: PMC11137940 DOI: 10.1186/s12967-024-05272-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 05/04/2024] [Indexed: 05/31/2024] Open
Abstract
The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.
Collapse
Affiliation(s)
- Francesco Campa
- Department of Biomedical Sciences, University of Padua, Padua, Italy.
| | - Giuseppe Coratella
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
| | - Giuseppe Cerullo
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| | - Zeasseska Noriega
- NEFC-Barcelona Sports Sciences Research Group, Institut Nacional d'Educació Física de Catalunya (INEFC), Universitat de Barcelona (UB), 08038, Barcelona, Spain
| | - Rubén Francisco
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz-Quebrada, Portugal
| | - Davide Charrier
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| | - Alfredo Irurtia
- NEFC-Barcelona Sports Sciences Research Group, Institut Nacional d'Educació Física de Catalunya (INEFC), Universitat de Barcelona (UB), 08038, Barcelona, Spain
| | - Henry Lukaski
- Department of Kinesiology and Public Health Education, Hyslop Sports Center, University of North Dakota, Grand Forks, USA
| | - Analiza Mónica Silva
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, Cruz-Quebrada, Portugal
| | - Antonio Paoli
- Department of Biomedical Sciences, University of Padua, Padua, Italy
| |
Collapse
|
|
9
|
Guglielmi V, Dalle Grave R, Leonetti F, Solini A. Female obesity: clinical and psychological assessment toward the best treatment. Front Endocrinol (Lausanne) 2024; 15:1349794. [PMID: 38765954 PMCID: PMC11099266 DOI: 10.3389/fendo.2024.1349794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 04/19/2024] [Indexed: 05/22/2024] Open
Abstract
Obesity is a heterogeneous condition which results from complex interactions among sex/gender, sociocultural, environmental, and biological factors. Obesity is more prevalent in women in most developed countries, and several clinical and psychological obesity complications show sex-specific patterns. Females differ regarding fat distribution, with males tending to store more visceral fat, which is highly correlated to increased cardiovascular risk. Although women are more likely to be diagnosed with obesity and appear more motivated to lose weight, as confirmed by their greater representation in clinical trials, males show better outcomes in terms of body weight and intra-abdominal fat loss and improvements in the metabolic risk profile. However, only a few relatively recent studies have investigated gender differences in obesity, and sex/gender is rarely considered in the assessment and management of the disease. This review summarizes the evidence of gender differences in obesity prevalence, contributing factors, clinical complications, and psychological challenges. In addition, we explored gender differences in response to obesity treatments in the specific context of new anti-obesity drugs.
Collapse
Affiliation(s)
- Valeria Guglielmi
- Unit of Internal Medicine and Obesity Center, Department of Systems Medicine, Policlinico Tor Vergata, University of Rome Tor Vergata, Rome, Italy
| | - Riccardo Dalle Grave
- Department of Eating and Weight Disorders, Villa Garda Hospital, Garda, VR, Italy
| | - Frida Leonetti
- Department of Medical-Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy
| | - Anna Solini
- Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, Pisa, Italy
| |
Collapse
|
|
10
|
Wong JMW, Ludwig DS, Allison DB, Baidwan N, Bielak L, Chiu CY, Dickinson SL, Golzarri-Arroyo L, Heymsfield SB, Holmes L, Jansen LT, Lesperance D, Mehta T, Sandman M, Steltz SK, Wong WW, Yu S, Ebbeling CB. Design and conduct of a randomized controlled feeding trial in a residential setting with mitigation for COVID-19. Contemp Clin Trials 2024; 140:107490. [PMID: 38458559 DOI: 10.1016/j.cct.2024.107490] [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: 12/19/2023] [Revised: 02/26/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Evaluating effects of different macronutrient diets in randomized trials requires well defined infrastructure and rigorous methods to ensure intervention fidelity and adherence. METHODS This controlled feeding study comprised two phases. During a Run-in phase (14-15 weeks), study participants (18-50 years, BMI, ≥27 kg/m2) consumed a very-low-carbohydrate (VLC) diet, with home delivery of prepared meals, at an energy level to promote 15 ± 3% weight loss. During a Residential phase (13 weeks), participants resided at a conference center. They received a eucaloric VLC diet for three weeks and then were randomized to isocaloric test diets for 10 weeks: VLC (5% energy from carbohydrate, 77% from fat), high-carbohydrate (HC)-Starch (57%, 25%; including 20% energy from refined grains), or HC-Sugar (57%, 25%; including 20% sugar). Outcomes included measures of body composition and energy expenditure, chronic disease risk factors, and variables pertaining to physiological mechanisms. Six cores provided infrastructure for implementing standardized protocols: Recruitment, Diet and Meal Production, Participant Support, Assessments, Regulatory Affairs and Data Management, and Statistics. The first participants were enrolled in May 2018. Participants residing at the conference center at the start of the COVID-19 pandemic completed the study, with each core implementing mitigation plans. RESULTS Before early shutdown, 77 participants were randomized, and 70 completed the trial (65% of planned completion). Process measures indicated integrity to protocols for weighing menu items, within narrow tolerance limits, and participant adherence, assessed by direct observation and continuous glucose monitoring. CONCLUSION Available data will inform future research, albeit with less statistical power than originally planned.
Collapse
Affiliation(s)
- Julia M W Wong
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America; Harvard Medical School, Boston, MA, United States of America
| | - David S Ludwig
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America; Harvard Medical School, Boston, MA, United States of America
| | - David B Allison
- Indiana University School of Public Health, Bloomington, IN, United States of America
| | - Navneet Baidwan
- Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, United States of America
| | - Lisa Bielak
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - Chia-Ying Chiu
- Division of Pulmonary, Allergy, and Acute Critical Care, Department of Medicine, University of Alabama at Birmingham, United States of America
| | - Stephanie L Dickinson
- Indiana University School of Public Health, Bloomington, IN, United States of America
| | | | - Steven B Heymsfield
- Metabolism & Body Composition Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, United States of America
| | - Lauren Holmes
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - Lisa T Jansen
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America; Harvard Medical School, Boston, MA, United States of America
| | - Donna Lesperance
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - Tapan Mehta
- Department of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, United States of America
| | - Megan Sandman
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - Sarah K Steltz
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - William W Wong
- USDA/ARS Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, United States of America
| | - Shui Yu
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America
| | - Cara B Ebbeling
- New Balance Foundation Obesity Prevention Center, Boston Children's Hospital, United States of America; Harvard Medical School, Boston, MA, United States of America.
| |
Collapse
|
|
11
|
Liu X, He M, Li Y. Adult obesity diagnostic tool: A narrative review. Medicine (Baltimore) 2024; 103:e37946. [PMID: 38669386 PMCID: PMC11049696 DOI: 10.1097/md.0000000000037946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024] Open
Abstract
Obesity is a complex chronic metabolic disorder characterized by abnormalities in lipid metabolism. Obesity is not only associated with various chronic diseases but also has negative effects on physiological functions such as the cardiovascular, endocrine and immune systems. As a global health problem, the incidence and prevalence of obesity have increased significantly in recent years. Therefore, understanding assessment methods and measurement indicators for obesity is critical for early screening and effective disease control. Current methods for measuring obesity in adult include density calculation, anthropometric measurements, bioelectrical impedance analysis, dual-energy X-ray absorptiometry, computerized imaging, etc. Measurement indicators mainly include weight, hip circumference, waist circumference, neck circumference, skinfold thickness, etc. This paper provides a comprehensive review of the literature to date, summarizes and analyzes various assessment methods and measurement indicators for adult obesity, and provides insights and guidance for the innovation of obesity assessment indicators.
Collapse
Affiliation(s)
- Xiaolong Liu
- School of Life & Environmental Sciences, Guilin University of Electronic Technology, Guilin, Guangxi, China
- School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi, China
- Rehabilitation College, Guilin Life and Health Career Technical College, Guilin, Guangxi, China
| | - Mengxiao He
- School of Physical Education and Health, Guilin University, Guilin, Guangxi, China
| | - Yi Li
- School of Physical Education and Health, Guilin University, Guilin, Guangxi, China
| |
Collapse
|
|
12
|
García Flores FI, Klünder Klünder M, López Teros MT, Muñoz Ibañez CA, Padilla Castañeda MA. Development and Validation of a Method of Body Volume and Fat Mass Estimation Using Three-Dimensional Image Processing with a Mexican Sample. Nutrients 2024; 16:384. [PMID: 38337669 PMCID: PMC10856961 DOI: 10.3390/nu16030384] [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: 11/06/2023] [Revised: 12/12/2023] [Accepted: 12/27/2023] [Indexed: 02/12/2024] Open
Abstract
Body composition assessment using instruments such as dual X-ray densitometry (DXA) can be complex and their use is often limited to research. This cross-sectional study aimed to develop and validate a densitometric method for fat mass (FM) estimation using 3D cameras. Using two such cameras, stereographic images, and a mesh reconstruction algorithm, 3D models were obtained. The FM estimations were compared using DXA as a reference. In total, 28 adults, with a mean BMI of 24.5 (±3.7) kg/m2 and mean FM (by DXA) of 19.6 (±5.8) kg, were enrolled. The intraclass correlation coefficient (ICC) for body volume (BV) was 0.98-0.99 (95% CI, 0.97-0.99) for intra-observer and 0.98 (95% CI, 0.96-0.99) for inter-observer reliability. The coefficient of variation for kinetic BV was 0.20 and the mean difference (bias) for BV (liter) between Bod Pod and Kinect was 0.16 (95% CI, -1.2 to 1.6), while the limits of agreement (LoA) were 7.1 to -7.5 L. The mean bias for FM (kg) between DXA and Kinect was -0.29 (95% CI, -2.7 to 2.1), and the LoA was 12.1 to -12.7 kg. The adjusted R2 obtained using an FM regression model was 0.86. The measurements of this 3D camera-based system aligned with the reference measurements, showing the system's feasibility as a simpler, more economical screening tool than current systems.
Collapse
Affiliation(s)
| | - Miguel Klünder Klünder
- Research Subdirectorate, Children’s Hospital of Mexico Federico Gómez, Dr. Marquez St. 162, Colonia Doctores, Mexico City 06720, Mexico
| | - Miriam Teresa López Teros
- Health Department, Santa Fe Campus, Iberoamerican University, Prol. Paseo de la Reforma, Zedec Sta Fé, Álvaro Obregón, Mexico City 01219, Mexico;
| | - Cristopher Antonio Muñoz Ibañez
- Institute of Advanced Materials for Sustainable Manufacturing, Tecnológico de Monterrey, Canal de Miramontes, Tlalpan, Mexico City 14380, Mexico;
| | - Miguel Angel Padilla Castañeda
- Applied Science and Technology Institute (ICAT), National Autonomous University of Mexico (UNAM), Mexico City 04510, Mexico
| |
Collapse
|
|
13
|
Martins PC, Alves Junior CAS, Silva AM, Silva DAS. Phase angle and body composition: A scoping review. Clin Nutr ESPEN 2023; 56:237-250. [PMID: 37344079 DOI: 10.1016/j.clnesp.2023.05.015] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/12/2023] [Accepted: 05/22/2023] [Indexed: 06/23/2023]
Abstract
The aim of the study was to map evidence on the association between phase angle (PhA) and body composition in populations healthy and clinical populations). A systematic search for information regarding the topic was conducted in nine electronic databases (CINAHL, LILACS, PubMed, SciELO, Scopus, SPORTDiscus, Science Direct, MEDLINE and Web of Science) between October and November 2021. Studies with different designs, which allowed extracting information about the relationship between PhA and body composition (body cell mass [BCM], muscle tissue, bone mineral content, lean mass, total fat mass, visceral fat, and lean soft tissue mass [LSTM]) were included. Of the total of 11,913 initially identified studies, 59 were included after reading titles, abstracts, full texts and references. Most studies (40.67%; n = 24) presented data from Brazilian samples. With regard to the design of studies, 15 (25.42%) had longitudinal design. The age group of studies was wide, with studies involved 3-year-old children and 88-year-old adults. Body fat mass was evaluated by 31 studies (52.54%) in which 11 observed inverse relationships, nine studies showed direct relationships and 11 observed no relationship. Regarding lean mass, muscle mass, and fat-free mass components, most studies observed direct relationship with PhA (n = 37; 86.04%). It could be concluded that the phase angle was directly associated with lean mass and muscle mass in different age groups (children, adolescents, adults and older adults) and in people with different health diagnoses (HIV, cancer, hemodialysis, sarcopenia and without the diagnosis of diseases). Regarding body fat and the other investigated components, there is not enough evidence to establish the direction of associations.
Collapse
Affiliation(s)
- Priscila Custódio Martins
- Research Center in Kinanthropometry and Human Performance, Sports Center, Federal University of Santa Catarina, Florianópolis, SC, 88040900, Brazil.
| | - Carlos Alencar Souza Alves Junior
- Research Center in Kinanthropometry and Human Performance, Sports Center, Federal University of Santa Catarina, Florianópolis, SC, 88040900, Brazil.
| | - Analiza Mónica Silva
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade Lisboa, Estrada da Costa, 1499-002 Cruz-Quebrada, Portugal.
| | - Diego Augusto Santos Silva
- Research Center in Kinanthropometry and Human Performance, Sports Center, Federal University of Santa Catarina, Florianópolis, SC, 88040900, Brazil.
| |
Collapse
|
|
14
|
Cimmino F, Petrella L, Cavaliere G, Ambrosio K, Trinchese G, Monda V, D’Angelo M, Di Giacomo C, Sacconi A, Messina G, Mollica MP, Catapano A. A Bioelectrical Impedance Analysis in Adult Subjects: The Relationship between Phase Angle and Body Cell Mass. J Funct Morphol Kinesiol 2023; 8:107. [PMID: 37606402 PMCID: PMC10443260 DOI: 10.3390/jfmk8030107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/22/2023] [Accepted: 07/26/2023] [Indexed: 08/23/2023] Open
Abstract
The correct assessment of body composition is essential for an accurate diagnostic evaluation of nutritional status. The body mass index (BMI) is the most widely adopted indicator for evaluating undernutrition, overweight, and obesity, but it is unsuitable for differentiating changes in body composition. In recent times, bioelectrical impedance analyses (BIA) have been proven as a more accurate procedure for the assessment of body composition. Furthermore, the efficiency of bioelectrical impedance vector analyses, as an indicator of nutritional status and hydration, has been demonstrated. By applying a bioimpedance analysis, it is possible to detect fat mass (FM), fat free mass (FFM), phase angle, and body cell mass (BCM). It is important to point out that phase angle and BCM are strongly associated with health status. The aim of this research was to examine body composition and the association between the phase angle and BCM in 87 subjects (14 males and 73 females), aged between 23 and 54 years, with BMIs ranging from 17.0 to 32.0 kg/m2, according to sex. The BMI results revealed that the majority of the assessed subjects were within the normal range and had a normal percentage of FM. Our data indicate that a direct relation exists between phase angle and cellular health and that these values increase almost linearly. Consequently, a high phase angle may be related to increased BCM values.
Collapse
Affiliation(s)
- Fabiano Cimmino
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
- Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA), Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy;
| | - Lidia Petrella
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
| | - Gina Cavaliere
- Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA), Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy;
- Department of Pharmaceutical Sciences, University of Perugia, 06126 Perugia, Italy
| | - Katia Ambrosio
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
| | - Giovanna Trinchese
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
| | - Vincenzo Monda
- Department of Movement Sciences and Wellbeing, University of Naples “Parthenope”, 80133 Naples, Italy;
| | - Margherita D’Angelo
- Department of Experimental Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy;
| | - Cristiana Di Giacomo
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
| | - Alessandro Sacconi
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
| | - Giovanni Messina
- Department of Clinical and Experimental Medicine, University of Foggia, 71122 Foggia, Italy;
| | - Maria Pina Mollica
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
- Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA), Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy;
- Task Force on Microbiome Studies, University of Naples Federico II, 80138 Naples, Italy
| | - Angela Catapano
- Department of Biology, University of Naples Federico II, 80126 Naples, Italy; (L.P.); (K.A.); (G.T.); (C.D.G.); (A.S.); (M.P.M.)
- Centro Servizi Metrologici e Tecnologici Avanzati (CeSMA), Complesso Universitario di Monte Sant’Angelo, 80126 Naples, Italy;
| |
Collapse
|
|
15
|
Czeck MA, Juckett WT, Roelofs EJ, Dengel DR. Total and regional dual X-ray absorptiometry derived four-compartment model. Clin Nutr ESPEN 2023; 55:185-190. [DOI: 10.1016/j.clnesp.2023.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 03/20/2023] [Indexed: 04/01/2023]
|
|
16
|
Bray GA. Beyond BMI. Nutrients 2023; 15:nu15102254. [PMID: 37242136 DOI: 10.3390/nu15102254] [Citation(s) in RCA: 65] [Impact Index Per Article: 32.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 05/04/2023] [Accepted: 05/06/2023] [Indexed: 05/28/2023] Open
Abstract
This review examined the origins of the concept of the BMI in the work of Quetelet in the 19th century and its subsequent adoption and use in tracking the course of the pandemic of obesity during the 20th century. In this respect, it has provided a valuable international epidemiological tool that should be retained. However, as noted in this review, the BMI is deficient in at least three ways. First, it does not measure body fat distribution, which is probably a more important guide to the risk of excess adiposity than the BMI itself. Second, it is not a very good measure of body fat, and thus its application to the diagnosis of obesity or excess adiposity in the individual patient is limited. Finally, the BMI does not provide any insights into the heterogeneity of obesity or its genetic, metabolic, physiological or psychological origins. Some of these mechanisms are traced in this review.
Collapse
Affiliation(s)
- George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
| |
Collapse
|
|
17
|
Sagayama H, Yamada Y, Kondo E, Tanabe Y, Uchizawa A, Shankaran M, Nyangau E, Evans WJ, Hellerstein M, Yasukata J, Higaki Y, Ohnishi T, Takahashi H. Skeletal muscle mass can be estimated by creatine (methyl-d 3) dilution and is correlated with fat-free mass in active young males. Eur J Clin Nutr 2023; 77:393-399. [PMID: 36376405 DOI: 10.1038/s41430-022-01237-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/31/2022] [Accepted: 11/01/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Assessing whole-body skeletal muscle mass (SMM) and fat-free mass (FFM) is essential for the adequate nutritional management and training evaluation of athletes and trained individuals. This study aimed to determine the relationship between SMM assessed using the creatine (methyl-d3) dilution (D3-creatine) method and SMM estimated by whole-body magnetic resonance imaging (MRI) in healthy young men undergoing exercise training. Additionally, we examined the association between FFM measured using the four-component (4C) method (FFM4C) and the total body protein value estimated using 4C (TBpro4C). METHODS AND RESULTS We analyzed the data of 29 males (mean age, 19.9 ± 1.8 years) who exercised regularly. SMM measurements were obtained using the D3-creatine method (SMMD3-creatine) and MRI (SMMMRI). The SMMD3-creatine adjusted to 4.3 g/SMM kg was significantly higher than SMMMRI (p < 0.01). The fit of the creatine pool size compared with SMMMRI was 5.0 g/SMMMRI kg. SMMMRI was significantly correlated with both SMMD3-creatine adjusted to 4.3 g/kg and 5.1 g/kg. TBpro4C was significantly lower than SMMMRI (p < 0.01). Contrastingly, FFM4C was significantly higher than SMMMRI (p < 0.01). CONCLUSIONS SMMD3-creatine adjusted to 4.3 g/SMM kg-a previously reported value-may differ for athletes and active young males. We believe that a value of 5.0-5.1 g/SMM kg better estimates the total muscle mass in this population. Traditional FFM estimation highly correlates with SMMMRI in well-trained young males, and the relationships appear strong enough for total body protein or SMM to be estimated through the FFM value.
Collapse
Affiliation(s)
- Hiroyuki Sagayama
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.
| | - Yosuke Yamada
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Emi Kondo
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.,Japan Society for the Promotion of Science, Tokyo, Japan
| | - Yoko Tanabe
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.,Japan Society for the Promotion of Science, Tokyo, Japan
| | - Akiko Uchizawa
- Japan Society for the Promotion of Science, Tokyo, Japan.,Graduate School of Comprehensive Human Science, University of Tsukuba, Ibaraki, Japan
| | - Mahalakshmi Shankaran
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA, USA
| | - Edna Nyangau
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA, USA
| | - William J Evans
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA, USA.,Department of Medicine, Division of Geriatrics, Duke University Medical Center, Durham, NC, USA
| | - Marc Hellerstein
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA, USA
| | - Jun Yasukata
- Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan
| | - Yasuki Higaki
- Faculty of Sports and Health Science, Fukuoka University, Fukuoka, Japan
| | | | - Hideyuki Takahashi
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan.,Japan Institute of Sports Sciences, Tokyo, Japan
| |
Collapse
|
|
18
|
Rossini-Venturini AC, Veras L, Abdalla PP, Santos APD, Tasinafo-Junior MF, Silva LSLD, Alves TC, Ferriolli E, Romo-Perez V, Garcia-Soidan JL, Mota J, Machado DRL. Multicompartment body composition analysis in older adults: a cross-sectional study. BMC Geriatr 2023; 23:87. [PMID: 36759773 PMCID: PMC9912531 DOI: 10.1186/s12877-023-03752-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/23/2022] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND During aging, changes occur in the proportions of muscle, fat, and bone. Body composition (BC) alterations have a great impact on health, quality of life, and functional capacity. Several equations to predict BC using anthropometric measurements have been developed from a bi-compartmental (2-C) approach that determines only fat mass (FM) and fat-free mass (FFM). However, these models have several limitations, when considering constant density, progressive bone demineralization, and changes in the hydration of the FFM, as typical changes during senescence. Thus, the main purpose of this study was to propose and validate a new multi-compartmental anthropometric model to predict fat, bone, and musculature components in older adults of both sexes. METHODS This cross-sectional study included 100 older adults of both sexes. To determine the dependent variables (fat mass [FM], bone mineral content [BMC], and appendicular lean soft tissue [ALST]) whole total and regional dual-energy X-ray absorptiometry (DXA) body scans were performed. Twenty-nine anthropometric measures and sex were appointed as independent variables. Models were developed through multivariate linear regression. Finally, the predicted residual error sum of squares (PRESS) statistic was used to measure the effectiveness of the predicted value for each dependent variable. RESULTS An equation was developed to simultaneously predict FM, BMC, and ALST from only four variables: weight, half-arm span (HAS), triceps skinfold (TriSK), and sex. This model showed high coefficients of determination and low estimation errors (FM: R2adj: 0.83 and SEE: 3.16; BMC: R2adj: 0.61 and SEE: 0.30; ALST: R2adj: 0.85 and SEE: 1.65). CONCLUSION The equations provide a reliable, practical, and low-cost instrument to monitor changes in body components during the aging process. The internal cross-validation method PRESS presented sufficient reliability in the model as an inexpensive alternative for clinical field use.
Collapse
Affiliation(s)
- Ana Claudia Rossini-Venturini
- College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil. .,Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil.
| | - Lucas Veras
- grid.5808.50000 0001 1503 7226The Research Centre in Physical Activity, Health, and Leisure (CIAFEL), University of Porto, Porto, Portugal ,grid.5808.50000 0001 1503 7226Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal
| | - Pedro Pugliesi Abdalla
- grid.11899.380000 0004 1937 0722College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil ,Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil
| | - André Pereira dos Santos
- grid.11899.380000 0004 1937 0722College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil ,Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil ,grid.11899.380000 0004 1937 0722School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Márcio Fernando Tasinafo-Junior
- Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil ,grid.11899.380000 0004 1937 0722School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Leonardo Santos Lopes da Silva
- Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil ,grid.11899.380000 0004 1937 0722School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil
| | - Thiago Cândido Alves
- Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil
| | - Eduardo Ferriolli
- grid.11899.380000 0004 1937 0722Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil ,grid.11899.380000 0004 1937 0722Laboratório de Investigação Médica em Envelhecimento (LIM-66), Serviço de Geriatria, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, Brazil
| | - Vicente Romo-Perez
- grid.6312.60000 0001 2097 6738Faculty of Education and Sport Sciences, University of Vigo, Vigo, Spain
| | - Jose Luis Garcia-Soidan
- grid.6312.60000 0001 2097 6738Faculty of Education and Sport Sciences, University of Vigo, Vigo, Spain
| | - Jorge Mota
- grid.5808.50000 0001 1503 7226The Research Centre in Physical Activity, Health, and Leisure (CIAFEL), University of Porto, Porto, Portugal ,grid.5808.50000 0001 1503 7226Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal
| | - Dalmo Roberto Lopes Machado
- grid.11899.380000 0004 1937 0722College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil ,Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil ,grid.5808.50000 0001 1503 7226The Research Centre in Physical Activity, Health, and Leisure (CIAFEL), University of Porto, Porto, Portugal ,grid.11899.380000 0004 1937 0722School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil ,grid.7157.40000 0000 9693 350XESEC - Universidade do Algarve. , Campus da Penha, Faro, Portugal
| |
Collapse
|
|
19
|
Bland VL, Bea JW, Going SB, Yaghootkar H, Arora A, Ramadan F, Funk JL, Chen Z, Klimentidis YC. Metabolically favorable adiposity and bone mineral density: a Mendelian randomization analysis. Obesity (Silver Spring) 2023; 31:267-278. [PMID: 36502291 DOI: 10.1002/oby.23604] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 08/23/2022] [Accepted: 08/30/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE This analysis assessed the putative causal association between genetically predicted percent body fat and areal bone mineral density (aBMD) and, more specifically, the association between genetically predicted metabolically "favorable adiposity" (MFA) and aBMD at clinically relevant bone sites. METHODS Mendelian randomization was used to assess the relationship of MFA and percent body fat with whole-body, lumbar spine, femoral neck, and forearm aBMD. Sex-stratified and age-stratified exploratory analyses were conducted. RESULTS In all MR analyses, genetically predicted MFA was inversely associated with aBMD for the whole body (β = -0.053, p = 0.0002), lumbar spine (β = -0.075; p = 0.0001), femoral neck (β = -0.045; p = 0.008), and forearm (β = -0.115; p = 0.001). This negative relationship was strongest in older individuals and did not differ by sex. The relationship between genetically predicted percent body fat and aBMD was nonsignificant across all Mendelian randomization analyses. Several loci that were associated at a genome-wide significance level (p < 5 × 10-8 ) in opposite directions with body fat and aBMD measures were also identified. CONCLUSIONS This study did not support the hypothesis that MFA protects against low aBMD. Instead, it showed that MFA may result in lower aBMD. Further research is needed to understand how MFA affects aBMD and other components of bone health such as bone turnover, bone architecture, and osteoporotic fractures.
Collapse
Affiliation(s)
- Victoria L Bland
- School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA
| | - Jennifer W Bea
- Department of Health Promotion Sciences, University of Arizona, Tucson, Arizona, USA
- The University of Arizona Cancer Center, Tucson, Arizona, USA
| | - Scott B Going
- School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA
| | - Hanieh Yaghootkar
- Centre for Inflammation Research and Translational Medicine, Department of Life Sciences, Brunel University London, Uxbridge, UK
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, Research, Innovation, Royal Devon & Exeter Hospital, Exeter, UK
| | - Amit Arora
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| | - Ferris Ramadan
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| | - Janet L Funk
- School of Nutritional Sciences and Wellness, University of Arizona, Tucson, Arizona, USA
- Department of Medicine, University of Arizona, Tucson, Arizona, USA
| | - Zhao Chen
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| | - Yann C Klimentidis
- Department of Epidemiology and Biostatistics, University of Arizona, Tucson, Arizona, USA
| |
Collapse
|
|
20
|
Cerqueira MS, Amorim PRS, Encarnação IGA, Rezende LMT, Almeida PHRF, Silva AM, Sillero-Quintana M, Silva DAS, Santos FK, Marins JCB. Equations based on anthropometric measurements for adipose tissue, body fat, or body density prediction in children and adolescents: a scoping review. Eat Weight Disord 2022; 27:2321-2338. [PMID: 35699918 DOI: 10.1007/s40519-022-01405-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/05/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE Assessing the body composition of children and adolescents is important to monitor their health status. Anthropometric measurements are feasible and less-expensive than other techniques for body composition assessment. This study aimed to systematically map anthropometric equations to predict adipose tissue, body fat, or density in children and adolescents, and to analyze methodological aspects of the development of anthropometric equations using skinfolds. METHODS A scoping review was carried out following the PRISMA-ScR criteria. The search was carried out in eight databases. The methodological structure protocol of this scoping review was retrospectively registered in the Open Science Framework ( https://osf.io/35uhc/ ). RESULTS We included 78 reports and 593 anthropometric equations. The samples consisted of healthy individuals, people with different diseases or disabilities, and athletes from different sports. Dual-energy X-ray absorptiometry (DXA) was the reference method most commonly used in developing equations. Triceps and subscapular skinfolds were the anthropometric measurements most frequently used as predictors in the equations. Age, stage of sexual maturation, and peak height velocity were used as complementary variables in the equations. CONCLUSION Our scoping review identified equations proposed for children and adolescents with a great diversity of characteristics. In many of the reports, important methodological aspects were not addressed, a factor that may be associated with equation bias. LEVEL IV Evidence obtained from multiple time series analysis such as case studies. (NB: dramatic results in uncontrolled trials might also be regarded as this type of evidence).
Collapse
Affiliation(s)
- Matheus S Cerqueira
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
- Academic Department of Education, Federal Institute of Education, Science and Technology of the Southeast of Minas Gerais, Campus Rio Pomba, Rio Pomba, Minas Gerais, Brazil
| | - Paulo R S Amorim
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| | - Irismar G A Encarnação
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.
- Higher School of Education, Polytechnic Institute of Bragança, Campus Santa Apolónia, Bragança, Portugal.
| | - Leonardo M T Rezende
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| | - Paulo H R F Almeida
- Graduate Program in Medicines and Pharmaceutical Services, Department of Social Pharmacy, Faculty of Pharmacy, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Analiza M Silva
- Exercise and Health Laboratory, CIPER, Faculty of Human Motricity, University of Lisbon, Lisbon, Portugal
| | - Manuel Sillero-Quintana
- Faculty of Sciences of Physical Activity and Sports, Polytechnic University of Madrid, Madrid, Spain
| | - Diego A S Silva
- Graduate Program in Physical Education, Federal University of Santa Catarina, Florianópolis, Santa Catarina, Brazil
| | - Fernanda K Santos
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| | - João C B Marins
- Department of Physical Education, Center for Biological and Health Sciences, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| |
Collapse
|
|
21
|
Rossini-Venturini AC, Abdalla PP, Fassini PG, dos Santos AP, Tasinafo Junior MF, Alves TC, Gomide EBG, de Pontes TL, Pfrimer K, Ferriolli E, Mota J, Beltran-Valls MR, Machado DRL. Association between classic and specific bioimpedance vector analysis and sarcopenia in older adults: a cross-sectional study. BMC Sports Sci Med Rehabil 2022; 14:170. [PMID: 36104722 PMCID: PMC9476257 DOI: 10.1186/s13102-022-00559-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/25/2022] [Indexed: 11/10/2022] Open
Abstract
Background To verify (1) the association between classic and specific bioelectrical impedance vector analysis (BIVA) with body composition, hydration, and physical performance in older adults with and without sarcopenia; (2) which BIVA most accurately distinguishes sarcopenia. Methods A sample of 94 older adults with and without sarcopenia (29 men and 65 women, 60–85 years) was evaluated. The classic and specific BIVA procedures, Dual energy X-ray absorptiometry (DXA), and deuterium dilution were performed. Sarcopenia was defined by muscle weakness and low skeletal muscle index, while severity was indicated by low physical performance. Results The BIVA's potential to monitor hydration and muscle mass loss in older adults seems feasible. Classic and specific BIVA were able to distinguish sarcopenia in women (p < 0.001), but not in men. When the sarcopenia criteria were individually analyzed, both classic and specific BIVA were able to distinguish low skeletal muscle index in women, while only classic BIVA did for men. For the criterion of slow physical performance, only the classic BIVA showed severity differences for women. The vectors of adults without sarcopenia of both sexes tended to be positioned in the left region of the ellipses, revealing a predominance of soft tissues. Conclusions Classic BIVA has a distinct sarcopenic association with body composition, hydration, and physical performance in older adults, while specific BIVA was similar between groups. Both BIVAs are sensible to detect female morphological changes (skeletal muscle index) but not for functional (handgrip, 6-min walk test) sarcopenia criteria. These procedures are promising tools for monitoring sarcopenia risks during aging.
Collapse
|
|
22
|
Gains in body mass and body water in pregnancy and relationships to birth weight of offspring in rural and urban Pune, India. J Nutr Sci 2022; 11:e75. [PMID: 36304819 PMCID: PMC9554425 DOI: 10.1017/jns.2022.75] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 12/14/2022] Open
Abstract
Maternal size, weight gain in pregnancy, fetal gender, environment and gestational age are known determinants of birth weight. It is not clear which component of maternal weight or gained weight during pregnancy influences birth weight. We evaluated the association of maternal total body water measured by the deuterium dilution technique (TBW-D2O) at 17 and 34 weeks of gestation with birth weight. A secondary aim was to examine the utility of bioimpedance spectroscopy (BIS) to determine total body water (TBW-BIS) in pregnancy. At 17 and 34 weeks of pregnancy, ninety-nine women (fifty-one rural and forty-eight urban) from Pune, India had measurements of body weight, TBW-D2O, TBW-BIS and offspring birth weight. At 17 weeks of gestation, average weights for rural and urban women were 45⋅5 ± 4⋅8 (sd) and 50⋅7 ± 7⋅8 kg (P < 0⋅0001), respectively. Maternal weight gains over the subsequent 17 weeks for rural and urban women were 6⋅0 ± 2⋅2 and 7⋅5 ± 2⋅8 kg (P = 0⋅003) and water gains were 4⋅0 ± 2⋅4 and 4⋅8 ± 2⋅8 kg (P = 0⋅092), respectively. In both rural and urban women, birth weight was positively, and independently, associated with gestation and parity. Only for rural women, between 17 and 34 weeks, was an increase in dry mass (weight minus TBW-D2O) or a decrease in TBW-D2O as a percentage of total weight associated with a higher birth weight. At both 17 and 34 weeks, TBW-BIS increasingly underestimated TBW-D2O as the water space increased. Differences in body composition during pregnancy between rural and urban environments and possible impacts of nutrition transition on maternal body composition and fetal growth were demonstrated.
Collapse
|
|
23
|
Are methods of estimating fat-free mass loss with energy-restricted diets accurate? Eur J Clin Nutr 2022; 77:525-531. [PMID: 36076068 DOI: 10.1038/s41430-022-01203-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 11/08/2022]
Abstract
BACKGROUND/OBJECTIVES Fat-free mass (FFM) often serves as a body composition outcome variable in weight loss studies. An important assumption is that the proportions of components that make up FFM remain stable following weight loss; some body composition models rely on these "constants". This exploratory study examined key FFM component proportions before and following weight loss in two studies of participants with overweight and obesity. SUBJECTS/METHODS 201 men and women consumed calorie-restricted moderate- or very-low carbohydrate diets leading to 10-18% weight loss in 9-15 weeks. Measured total body fat, lean mass, bone mineral, total body water (TBW), and body weight at baseline and follow-up were used to derive FFM and its chemical proportions using a four-component model. RESULTS A consistent finding in both studies was a non-significant reduction in bone mineral and a corresponding increase (p < 0.001) in bone mineral/FFM; FFM density increased significantly in one group of women and in all four participant groups combined (both, p < 0.05). FFM hydration (TBW/FFM) increased in all groups of men and women, one significantly (p < 0.01), and in the combined sample (borderline, p < 0.10). The proportion of FFM as protein decreased across all groups, two significantly (p < 0.05-0.01) and in the combined sample (p < 0.05). CONCLUSION FFM relative proportions of chemical components may not be identical before and after short-term weight loss, an observation impacting some widely used body composition models and methods. Caution is thus needed when applying FFM as a safety signal or to index metabolic evaluations in clinical trials when these body composition approaches are used.
Collapse
|
|
24
|
Cataldi D, Bennett JP, Quon BK, Liu YE, Heymsfield SB, Kelly T, Shepherd JA. Agreement and Precision of Deuterium Dilution for Total Body Water and Multicompartment Body Composition Assessment in Collegiate Athletes. J Nutr 2022; 152:2048-2059. [PMID: 35665820 DOI: 10.1093/jn/nxac116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 03/11/2022] [Accepted: 05/24/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Deuterium oxide (D2O) dilution is the criterion method for total body water (TBW) measurement, but results may vary depending on the specimen type, analysis method, and analyzing laboratory. Bioelectrical impedance (BIA) estimates TBW, but results may vary by device make and model. OBJECTIVES We investigated the accuracy and precision of TBW estimates and how measurement conditions affected the accuracy of body composition using multicompartment body composition models. METHODS Eighty collegiate athletes received duplicate TBW measures acquired from 3 BIA devices (S10, SFB7, and SOZO) and from unique D2O combinations of specimen type (saliva, urine), analysis methodology [Fourier transform infrared spectrophotometry (FTIR), isotope-ratio mass spectrometry (IRMS)], and 3 different laboratories. TBW measures were substituted into 2-compartment (2C) and 5-compartment (5C) body composition models. Criterion measures were compared using Lin's concordance correlation coefficient cutoff of poor (<0.90), moderate (0.90-0.95), substantial (0.95-0.99), and almost perfect (>0.99). RESULTS Fifty-one participants (26 female) completed the protocol. Using IRMS saliva as the criterion TBW, all other measures produced a substantial or almost perfect agreement, except for SFB7 (poor) and SOZO (moderate). The 2C body composition measures using D2O and BIA produced poor agreement except for moderate agreement for lab 3 FTIR saliva. The 5C body composition measures using D2O produced a substantial agreement, whereas the BIA device S10 and SOZO had a moderate agreement, while the SFB7 had a poor agreement to the criterion. Test-retest precision varied between techniques from 0.3% to 1.2% for TBW. CONCLUSIONS Small differences in TBW measurement led to significant differences in 2C models. The 5C models partially mitigate differences seen in 2C models when different TBW measures are used. Interchanging TBW measures in multicompartment models can be problematic and should be performed with these considerations.
Collapse
Affiliation(s)
- Devon Cataldi
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Jonathan P Bennett
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Brandon K Quon
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Young En Liu
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, Department of Metabolism & Body Composition, Baton Rouge, LA, USA
| | | | - John A Shepherd
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, HI, USA
| |
Collapse
|
|
25
|
Ribeiro da Costa JR, da Costa RF, Goncalves CAM, de Oliveira Borges MV, Almeida-Neto PFD, De Assis GG, Cabral BGDAT, Dantas PMS. The Body Adiposity Index is not applicable to the Brazilian adult population. Front Nutr 2022; 9:888507. [PMID: 36091231 PMCID: PMC9453421 DOI: 10.3389/fnut.2022.888507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 06/24/2022] [Indexed: 11/16/2022] Open
Abstract
Background Obesity is a serious disease that burdens public health systems around the world. It is a risk factor for the development of several non-communicable chronic diseases that are related to the amount and distribution of body fat. Body composition assessment using simple and low-cost techniques can help in the early detection of excess fat, allowing for the prevention and treatment of both obesity and associated diseases. Thus, identifying and proposing valid anthropometric indices for this purpose can be a great ally of health programs. Objective To verify the validity of the Body Adiposity Index (BAI) in relation to Dual Energy X-Ray Absorptiometry (DXA) for estimating body fat percentage in Brazilian adults, as well as to propose a new mathematical model to estimate the fat-free mass of this population. Methods In a cross-sectional study, 424 subjects (of which 220 were women), aged between 20 and 59 years, were evaluated by BAI and DXA, then randomly divided into two groups stratified by sex: the development group (n = 283) and the cross-validation group (n = 141). Statistical analyses to test the validity of BAI as a predictor of fat mass, in addition to proposing a new mathematical model for estimating fat-free mass, using DXA as a reference method. The analysis included paired t-test, stepwise multiple regression, coefficient of concordance correlation, and Bland-Altman plots. Results The BAI validity analysis showed a low correlation coefficient of agreement [CCC = 0.626; ρ (precision) = 0.795; Cb(accuracy) = 0.787]; in addition, the mean difference in the Bland-Altman plot was different from zero in the cross-validation group (p < 0.01) and limits of agreement (LOA) ranged between−8.0 and 14.4 kg, indicating a poor agreement between the BAI and the reference method. The new mathematical model for estimating FFM showed a high correlation coefficient of agreement (CCC = 0.952; ρ = 0.953; Cb = 0.999), in addition to acceptable LOA in the Bland-Altman plot (-6.7 and 6.7). Conclusion In the studied sample, the BAI showed low validity for estimating body fat, while the new proposed model was found to be a good option to assess the body composition of Brazilian adults.
Collapse
Affiliation(s)
| | | | | | | | - Paulo Francisco De Almeida-Neto
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil
- *Correspondence: Paulo Francisco De Almeida-Neto
| | - Gilmara Gomes De Assis
- Department of Physical Education, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | | |
Collapse
|
|
26
|
Tracking changes in body composition: comparison of methods and influence of pre-assessment standardisation. Br J Nutr 2022; 127:1656-1674. [PMID: 34325758 DOI: 10.1017/s0007114521002579] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The present study reports the validity of multiple assessment methods for tracking changes in body composition over time and quantifies the influence of unstandardised pre-assessment procedures. Resistance-trained males underwent 6 weeks of structured resistance training alongside a hyperenergetic diet, with four total body composition evaluations. Pre-intervention, body composition was estimated in standardised (i.e. overnight fasted and rested) and unstandardised (i.e. no control over pre-assessment activities) conditions within a single day. The same assessments were repeated post-intervention, and body composition changes were estimated from all possible combinations of pre-intervention and post-intervention data. Assessment methods included dual-energy X-ray absorptiometry (DXA), air displacement plethysmography, three-dimensional optical imaging, single- and multi-frequency bioelectrical impedance analysis, bioimpedance spectroscopy and multi-component models. Data were analysed using equivalence testing, Bland-Altman analysis, Friedman tests and validity metrics. Most methods demonstrated meaningful errors when unstandardised conditions were present pre- and/or post-intervention, resulting in blunted or exaggerated changes relative to true body composition changes. However, some methods - particularly DXA and select digital anthropometry techniques - were more robust to a lack of standardisation. In standardised conditions, methods exhibiting the highest overall agreement with the four-component model were other multi-component models, select bioimpedance technologies, DXA and select digital anthropometry techniques. Although specific methods varied, the present study broadly demonstrates the importance of controlling and documenting standardisation procedures prior to body composition assessments across distinct assessment technologies, particularly for longitudinal investigations. Additionally, there are meaningful differences in the ability of common methods to track longitudinal body composition changes.
Collapse
|
|
27
|
Maeda SS, Peters BSE, Martini LA, Antunes HKM, Gonzalez MC, Arantes HP, Prado CM, Pinto CL, de Araújo IM, de Paula FJA, Borges JLC, Albergaria BH, Ushida M, de Souza GC, de Mendonça LMC, do Prado M, de Medeiros Pinheiro M. Official position of the Brazilian Association of Bone Assessment and Metabolism (ABRASSO) on the evaluation of body composition by densitometry: part I (technical aspects)—general concepts, indications, acquisition, and analysis. Adv Rheumatol 2022; 62:7. [DOI: 10.1186/s42358-022-00241-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Accepted: 03/04/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Objective
To review the technical aspects of body composition assessment by dual-energy X-ray absorptiometry (DXA) and other methods based on the most recent scientific evidence.
Materials and methods
This Official Position is a result of efforts by the Scientific Committee of the Brazilian Association of Bone Assessment and Metabolism (Associação Brasileira de Avaliação Óssea e Osteometabolismo, ABRASSO) and health care professionals with expertise in body composition assessment who were invited to contribute to the preparation of this document. The authors searched current databases for relevant publications. In this first part of the Official Position, the authors discuss the different methods and parameters used for body composition assessment, general principles of DXA, and aspects of the acquisition and analysis of DXA scans.
Conclusion
Considering aspects of accuracy, precision, cost, duration, and ability to evaluate all three compartments, DXA is considered the gold-standard method for body composition assessment, particularly for the evaluation of fat mass. In order to ensure reliable, adequate, and reproducible DXA reports, great attention is required regarding quality control procedures, preparation, removal of external artifacts, imaging acquisition, and data analysis and interpretation.
Collapse
|
|
28
|
da Costa RF, Silva AM, Masset KVDSB, Cesário TDM, Cabral BGDAT, Ferrari G, Dantas PMS. Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance. Front Nutr 2022; 9:820736. [PMID: 35369072 PMCID: PMC8969741 DOI: 10.3389/fnut.2022.820736] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/15/2022] [Indexed: 01/31/2023] Open
Abstract
The bioelectrical impedance analysis (BIA) is one of the most commonly used techniques for assessing body composition in a clinical setting and in field approaches, as it has the advantages of easy application, fast, and non-invasive, in addition to its relatively low cost. However, the available predictive equations need to be valid for the evaluated subjects. The aim of this study was to verify the validity of several published BIA equations in estimating fat-free mass (FFM) among Brazilian adolescents, in addition to developing and cross-validating a BIA equation to estimate FFM appropriate for Brazilian adolescents. This is a cross-sectional study with 257 adolescents (128 girls) aged 10-19 years, randomly divided into two groups, namely, development (n = 172) and cross-validation (n = 85). The standard technique for assessing FFM was dual X-ray absorptiometry (DXA). The paired t-test, multiple regression, and the Bland-Altman plots were used to test the validity of the proposed models and to perform cross-validation of the model. The equation derived in this study was as follows: FFM = -17.189 + 0.498 (Height2/Resistance) + 0.226 Weight + 0.071 Reactance - 2.378 Sex + 0.097 Height + 0.222 Age; r 2 = 0.92; standard error of the estimate = 2.49 kg; the new equation for FFM showed better agreement when compared with that of the equations developed in other countries. In conclusion, the newly developed equations provide a valid FFM estimation and are recommended for Brazilian adolescents with similar characteristics.
Collapse
Affiliation(s)
- Roberto Fernandes da Costa
- Physical Education Department, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil,*Correspondence: Roberto Fernandes da Costa,
| | - Analiza M. Silva
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | | | - Tatianny de Macêdo Cesário
- Physical Education Department, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | - Gerson Ferrari
- Escuela de Ciencias de la Actividad Física, el Deporte y la Salud, Universidad de Santiago de Chile (USACH), Santiago, Chile,Grupo de Estudio en Educación, Laboratorio de Rendimiento Humano, Actividad Física y Salud (GEEAFyS), Universidad Católica del Maule, Talca, Chile
| | - Paulo Moreira Silva Dantas
- Physical Education Department, Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil
| |
Collapse
|
|
29
|
Burridge K, Christensen SM, Golden A, Ingersoll AB, Tondt J, Bays HE. Obesity history, physical exam, laboratory, body composition, and energy expenditure: An Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) 2022. OBESITY PILLARS (ONLINE) 2022; 1:100007. [PMID: 37990700 PMCID: PMC10661987 DOI: 10.1016/j.obpill.2021.100007] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 12/23/2021] [Indexed: 11/23/2023]
Abstract
Background This Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on History, Physical Exam, Body Composition and Energy Expenditure is intended to provide clinicians an overview of the clinical and diagnostic evaluation of patients with pre-obesity/obesity. Methods The scientific information for this CPS is based upon published scientific citations, clinical perspectives of OMA authors, and peer review by the Obesity Medicine Association leadership. Results This CPS outlines important components of medical, dietary, and physical activity history as well as physical exams, with a focus on specific aspects unique to managing patients with pre-obesity or obesity. Patients with pre-obesity/obesity benefit from the same preventive care and general laboratory testing as those without an increase in body fat. In addition, patients with pre-obesity/obesity may benefit from adiposity-specific diagnostic testing - both generally and individually - according to patient presentation and clinical judgment. Body composition testing, such as dual energy x-ray absorptiometry, bioelectrical impedance, and other measures, each have their own advantages and disadvantages. Some patients in clinical research, and perhaps even clinical practice, may benefit from an assessment of energy expenditure. This can be achieved by several methods including direct calorimetry, indirect calorimetry, doubly labeled water, or estimated by equations. Finally, a unifying theme regarding the etiology of pre-obesity/obesity and effectiveness of treatments of obesity centers on the role of biologic and behavior efficiencies and inefficiencies, with efficiencies more often associated with increases in fat mass and inefficiencies more often associated with decreases in fat mass. Conclusion The Obesity Medicine Association (OMA) Clinical Practice Statement (CPS) on History, Physical Exam, Body Composition and Energy Expenditure is one of a series of OMA CPSs designed to assist clinicians in the care of patients with the disease of pre-obesity/obesity.
Collapse
Affiliation(s)
- Karlijn Burridge
- Gaining Health, 528 Pennsylvania Ave #708 Glen Ellyn, IL 60137, USA
| | - Sandra M. Christensen
- Integrative Medical Weight Management, 2611 NE 125th St., Suite 100B, Seattle, WA, 98125, USA
| | - Angela Golden
- NP Obesity Treatment Clinic and NP from Home, LLC, PO Box 25959, Munds Park, AZ, 86017, USA
| | - Amy B. Ingersoll
- Enara Health, 3050 S. Delaware Street, Suite 130, San Mateo, CA, 94403, USA
| | - Justin Tondt
- Department of Family and Community Medicine, Eastern Virginia Medical School, P.O. Box 1980, Norfolk, VA, 23501, USA
| | - Harold E. Bays
- Louisville Metabolic and Atherosclerosis Research Center, 3288 Illinois Avenue, Louisville, KY, 40213, USA
- University of Louisville School of Medicine, USA
| |
Collapse
|
|
30
|
Gobbo LA, Langer RD, Marini E, Buffa R, Borges JH, Pascoa MA, Cirolini VX, Guerra-Júnior G, Gonçalves EM. Effect of Physical Training on Body Composition in Brazilian Military. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031732. [PMID: 35162755 PMCID: PMC8834877 DOI: 10.3390/ijerph19031732] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/24/2022] [Accepted: 01/29/2022] [Indexed: 01/10/2023]
Abstract
The military are selected on the basis of physical standards and are regularly involved in strong physical activities, also related to particular sports training. The aims of the study were to analyze the effect of a 7-month military training program on body composition variables and the suitability of specific ‘bioelectrical impedance vector analysis’ (spBIVA), compared to DXA, to detect the changes in body composition. A sample of 270 male Brazilian cadets (19.1 ± 1.1 years), composed of a group practicing military physical training routine only (MT = 155) and a group involved in a specific sport training (SMT = 115), were measured by body composition assessments (evaluated by means of DXA and spBIVA) at the beginning and the end of the military routine year. The effect of training on body composition was similar in SMT and MT groups, with an increase in LST. DXA and spBIVA were correlated, with specific resistance (Rsp) and reactance (Xcsp) positively related to fat mass (FM), FM%, LST, and lean soft tissue index (LSTI), and phase angle positively related to LST and LSTI. Body composition variations due to physical training were recognized by spBIVA: the increase in muscle mass was indicated by the phase angle and Xcsp increase, and the stability of FM% was consistent with the unchanged values of Rsp. Military training produced an increase in muscle mass, but no change in FM%, independently of the sample characteristics at baseline and the practice of additional sports. SpBIVA is a suitable technique for the assessment of body composition in military people.
Collapse
Affiliation(s)
- Luis Alberto Gobbo
- Skeletal Muscle Assessment Laboratory (LABSIM), School of Technology and Science, São Paulo State University (UNESP), Presidente Prudente 19060-900, SP, Brazil;
| | - Raquel David Langer
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| | - Elisabetta Marini
- Department of Life and Environmental Sciences, University of Cagliari, 09042 Monserrato, Italy;
- Correspondence: ; Tel.: +39-070-675-6607
| | - Roberto Buffa
- Department of Life and Environmental Sciences, University of Cagliari, 09042 Monserrato, Italy;
| | - Juliano Henrique Borges
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| | - Mauro A. Pascoa
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| | - Vagner X. Cirolini
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| | - Gil Guerra-Júnior
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| | - Ezequiel Moreira Gonçalves
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas 13083-887, SP, Brazil; (R.D.L.); (J.H.B.); (M.A.P.); (V.X.C.); (G.G.-J.); (E.M.G.)
| |
Collapse
|
|
31
|
Schlösser L, Delgado FSG, Silva LVD, Copetti CLK, Pietro PFD, Hinnig PDF, Carvalho JD, Moreno YMF, Hansen F. Validity of body fat percentage through different methods of body composition assessment in elite soccer referees. REVISTA BRASILEIRA DE CINEANTROPOMETRIA E DESEMPENHO HUMANO 2022. [DOI: 10.1590/1980-0037.2022v24e84121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
abstract The arbitration exercise in a soccer game requires high physical fitness and all federations apply physical tests to referees, including anthropometric tests, classifying them as fit or not for the role. The aim of this study was to assess the validity of the total body fat percentage (%BF) through different evaluation methods of body composition referenced in a four-compartment (4C) model. Cross-sectional study performed in 2018 with 21 elite male referees. %BF was estimated by 4 methods: anthropometry; bioelectrical impedance analysis (BIA); Dual X-ray absorptiometry (DXA) and air displacement plethysmography (ADP). Moreover, three and four-compartment (3 and 4C) models were calculated. Bland–Altman and intraclass correlations (ICC) analysis were performed to determine validity of all methods compared to a 4C reference. The results of one-way ANOVA revealed that there was no significant difference (F=1.541; p=0.182) between %BF analyzed by 4C model (15.98 ± 6.20), anthropometry (mean ± SD, 18.46 ± 7.03), ADP (16.19 ± 6.24), BIA (16.67 ± 5.30), DXA (20.33 ± 6.56) and 3C (16.92 ± 5.53). The Bland–Altman analysis showed that all methods analyzed overestimate %BF compared to the 4C model. The best agreement was obtained from the ADP evaluation (bias=-0.2), followed by BIA (bias=-0.6), 3C (bias=-0.9), anthropometry (bias=-2.4) and DXA (bias=-4.3). Validation assessed by ICC was excellent (ICC≥0.90) in most methods, except for anthropometry (ICC=0.80) and DXA (ICC=0.71). Overall, the results suggest that ADP, BIA and 3C were the best method to %BF evaluation. Nevertheless, anthropometry remains as a feasible method to monitor %BF of elite soccer referees.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | - Fernanda Hansen
- Federal University of Santa Catarina, Brazil; Federal University of Santa Catarina, Brazil
| |
Collapse
|
|
32
|
Heymsfield SB, Smith B, Wong M, Bennett J, Ebbeling C, Wong JMW, Strauss BJG, Shepherd J. Multicomponent density models for body composition: Review of the dual energy X-ray absorptiometry volume approach. Obes Rev 2021; 22:e13274. [PMID: 34101964 PMCID: PMC11419666 DOI: 10.1111/obr.13274] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 04/19/2021] [Indexed: 11/27/2022]
Abstract
Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air-displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual-energy X-ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual-energy X-ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air-displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual-energy X-ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.
Collapse
Affiliation(s)
| | - Brooke Smith
- Pennington Biomedical Research Center, LSU System, Baton Rouge, LA, USA
| | - Michael Wong
- Cancer Center, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Jonathan Bennett
- Cancer Center, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Cara Ebbeling
- New Balance Foundation Obesity Prevention Center, Boston Children’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Julia M. W. Wong
- New Balance Foundation Obesity Prevention Center, Boston Children’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Boyd J. G. Strauss
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia
| | - John Shepherd
- Cancer Center, University of Hawaii Cancer Center, Honolulu, HI, USA
| |
Collapse
|
|
33
|
Costa RFD, Masset KVDSB, Silva AM, Cabral BGDAT, Dantas PMS. Development and cross-validation of predictive equations for fat-free mass and lean soft tissue mass by bioelectrical impedance in Brazilian women. Eur J Clin Nutr 2021; 76:288-296. [PMID: 34230624 DOI: 10.1038/s41430-021-00946-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 05/07/2021] [Accepted: 05/17/2021] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Bioelectrical impedance is one of the most used clinical techniques to assess body composition; however, it is necessary that the available predictive equations are valid for the evaluated subjects. This study aimed to develop and cross-validate equations for fat-free mass (FFM) and lean soft tissue mass (LSTM) by bioelectrical impedance for Brazilian women, in addition to test the validity of other available equations. SUBJECTS/METHODS Cross-sectional study with 222 women aged 20-59 years, randomly divided into two groups: development and cross-validation. The standard technique for assessing fat mass, FFM and LSTM was dual energy X-ray absorptiometry. Paired t test, multiple regression, and Bland-Altman plots were used to test the validity of the proposed models, as well as to perform cross-validation of the models. RESULTS The equations derived in this study were: FFM = 16.284 + 0.442 × (Height2/Resistance) - 0.13 × age + 0.302 × Weight - 0.121 × Waist Circumference; r2 = 0.86; SEE = 2.32 kg; and LSTM = 14.732 + 0.427 × (Height2/Resistance) - 0.125 × age + 0.291 × Weight - 0.115 × Waist Circumference; r2 = 0.92; SEE = 2.29 kg. In addition, the new equation for FFM showed better agreement when compared to another equation developed for a Brazilian population. CONCLUSIONS The newly developed equations provide a valid FFM and LSTM estimation and are recommended for Brazilian women with similar characteristics.
Collapse
Affiliation(s)
- Roberto Fernandes da Costa
- Physical Education Department, Health Sciences Centre, Universidade Federal do Rio Grande do Norte, Natal, Brazil.
| | | | - Analiza M Silva
- Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade de Lisboa, Lisbon, Portugal
| | | | - Paulo Moreira Silva Dantas
- Physical Education Department, Health Sciences Centre, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| |
Collapse
|
|
34
|
Metabolic Dysfunction in Spinal Muscular Atrophy. Int J Mol Sci 2021; 22:ijms22115913. [PMID: 34072857 PMCID: PMC8198411 DOI: 10.3390/ijms22115913] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/25/2021] [Accepted: 05/29/2021] [Indexed: 12/11/2022] Open
Abstract
Spinal muscular atrophy (SMA) is an autosomal recessive genetic disorder leading to paralysis, muscle atrophy, and death. Significant advances in antisense oligonucleotide treatment and gene therapy have made it possible for SMA patients to benefit from improvements in many aspects of the once devastating natural history of the disease. How the depletion of survival motor neuron (SMN) protein, the product of the gene implicated in the disease, leads to the consequent pathogenic changes remains unresolved. Over the past few years, evidence toward a potential contribution of gastrointestinal, metabolic, and endocrine defects to disease phenotype has surfaced. These findings ranged from disrupted body composition, gastrointestinal tract, fatty acid, glucose, amino acid, and hormonal regulation. Together, these changes could have a meaningful clinical impact on disease traits. However, it is currently unclear whether these findings are secondary to widespread denervation or unique to the SMA phenotype. This review provides an in-depth account of metabolism-related research available to date, with a discussion of unique features compared to other motor neuron and related disorders.
Collapse
|
|
35
|
Making the choice between bioelectrical impedance measures for body hydration status assessment. Sci Rep 2021; 11:7685. [PMID: 33833322 PMCID: PMC8032770 DOI: 10.1038/s41598-021-87253-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 03/25/2021] [Indexed: 02/07/2023] Open
Abstract
Situational or persistent body fluid deficit (i.e., de- or hypo-hydration) is considered a significant health risk factor. Bioimpedance analysis (BIA) has been suggested as an alternative to less reliable subjective and biochemical indicators of hydration status. The present study aimed to compare various BIA models in the prediction of direct measures of body compartments associated with hydration/osmolality. Fish (n = 20) was selected as a biological model for physicochemically measuring proximate body compartments associated with hydration such as water, dissolved proteins, and non-osseous minerals as the references or criterion points. Whole-body and segmental/local impedance measures were used to investigate a pool of BIA models, which were compared by Akaike Information Criterion in their ability to accurately predict the body components. Statistical models showed that ‘volumetric-based’ BIA measures obtained in parallel, such as distance2/Rp, could be the best approach in predicting percent of body moisture, proteins, and minerals in the whole-body schema. However, serially-obtained BIA measures, such as the ratio of the reactance to resistance and the resistance adjusted for distance between electrodes, were the best fitting in predicting the compartments in the segmental schema. Validity of these results should be confirmed on humans before implementation in practice.
Collapse
|
|
36
|
Stagi S, Irurtia A, Rosales Rafel J, Cabras S, Buffa R, Carrasco-Marginet M, Castizo-Olier J, Marini E. Segmental body composition estimated by specific BIVA and dual-energy X-ray absorptiometry. Clin Nutr 2021; 40:1621-1627. [PMID: 33752150 DOI: 10.1016/j.clnu.2021.02.043] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/25/2021] [Accepted: 02/27/2021] [Indexed: 11/19/2022]
Abstract
AIMS The aim of this study was to analyse the association between specific bioelectric impedance vector analysis (BIVA) and dual-energy X-ray absorptiometry (DXA) to assess segmental body composition using DXA as the reference technique. METHODS The sample comprised 50 young active students who practised or played different sports (25 men, age: 24.37 ± 4.79 y; 25 women, age: 24.32 ± 4.43 y) from the National Institute of Physical Education of Catalonia (INEFC). Anthropometric data (height, weight, arm, waist, and calf circumferences) and bioelectrical measurements (R, ohm; Xc, ohm) were recorded. Body composition was analysed with specific BIVA. DXA was used as the reference method to assess body composition of the whole-body, the trunk, and the limbs. The percentage of fat mass (%FMDXA) and fat-free mass index (FFMIDXA = FFM/length2) were calculated. The agreement between specific BIVA and DXA was evaluated by a depth-depth analysis, two-way ANOVA, and Pearson's correlations. RESULTS The depth-depth analysis showed a good agreement between DXA and BIVA (F = 14.89, p < 0.001) in both sexes and all body segments. Specific vector length (Zsp; i.e. indicative of %FM) was correlated with %FMDXA in the whole body and all body segments, and the phase angle was correlated with FFMIDXA, with he trunk in women as the only exception. Specific BIVA demonstrated to balance the effect of body size on bioelectrical measurements in both whole and segmental approaches. CONCLUSIONS Segmental specific BIVA and DXA provided a consistent evaluation of body composition in both sexes, of the whole body and each body segment. The indices %FM and FFMI obtained with DXA were correlated to vector length and phase angle in each segment, respectively. Specific BIVA represents a promising technique for monitoring segmental body composition changes in sport science and clinical applications.
Collapse
Affiliation(s)
- Silvia Stagi
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, Cagliari, 09042, Italy.
| | - Alfredo Irurtia
- Department of Sports Performance, National Institute of Physical Education of Catalonia, University of Barcelona, Barcelona, Spain
| | - Joaquim Rosales Rafel
- Faixat Body Scan Sport Department, Avinguda de L'Estadi, 12-22, Barcelona, 08038, Spain
| | - Stefano Cabras
- Department of Statistics, Universidad Carlos III de Madrid, Getafe, Spain
| | - Roberto Buffa
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, Cagliari, 09042, Italy
| | - Marta Carrasco-Marginet
- Department of Health and Applied Sciences, National Institute of Physical Education of Catalonia, University of Barcelona, Barcelona, Spain
| | - Jorge Castizo-Olier
- School of Health Sciences, Tecnocampus Mataró-Maresme, Pompeu Fabra University, Mataró, Spain
| | - Elisabetta Marini
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, Cagliari, 09042, Italy.
| |
Collapse
|
|
37
|
Comparison of body composition assessment across body mass index categories by two multifrequency bioelectrical impedance analysis devices and dual-energy X-ray absorptiometry in clinical settings. Eur J Clin Nutr 2021; 75:1275-1282. [PMID: 33483630 DOI: 10.1038/s41430-020-00839-5] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 11/16/2020] [Accepted: 12/07/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND InBody-770 and SECA mBCA 515 are multifrequency bioelectrical impedance analysis (BIA) devices, which are commonly used in the clinic to assess fat-free mass (FFM) and body fat (BF). However, the accuracy between devices in clinical settings, across different body mass index (BMI) groups remains unclear. METHODS Body composition for 226 participants (51% men, aged 18-80 years, BMI 18-56 kg/m²) was assessed by two commercial multifrequency BIA devices requiring standing position and using eight-contact electrodes, InBody 770 and SECA mBCA 515, and compared to results from dual-energy X-ray absorptiometry (DXA). Measurements were performed in a random order, after a 3 h fast and no prior exercise. Lin's-concordance correlation and Bland-Altman analyses were used to compare between devices, and linear regression to assess accuracy in BF% across BMI groups. RESULTS We found strong correlation between DXA results for study population BF% and those obtained by InBody (ρc = 0.922, 95% confidence interval (CI) 0.902, 0.938) and DXA and SECA (ρc = 0.940, CI 0.923, 0.935), with 95% limits of agreements between 2.6 and -8.9, and 7.1 and -7.6, respectively. BF% assessment by SECA was similar to DXA (-0.3%, p = 0.267), and underestimated by InBody (-3.1%, p < 0.0001). InBody deviations were largest among normal weight people and decreased with increasing BMI group, while SECA measurements remained unaffected. CONCLUSIONS Both BIA devices agreed well with BF% assessment obtained by DXA. Unlike SECA, InBody underestimated BF% in both genders and was influenced by BMI categories. Therefore, in clinical settings, individual assessment of BF% should be taken with caution.
Collapse
|
|
38
|
Five-component model validation of reference, laboratory and field methods of body composition assessment. Br J Nutr 2020; 125:1246-1259. [PMID: 32921319 DOI: 10.1017/s0007114520003578] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
This study reports the validity of body fat percentage (BF%) estimates from several commonly employed techniques as compared with a five-component (5C) model criterion. Healthy adults (n 170) were assessed by dual-energy X-ray absorptiometry (DXA), air displacement plethysmography (ADP), multiple bioimpedance techniques and optical scanning. Output was also used to produce a criterion 5C model, multiple variants of three- and four-component models (3C; 4C) and anthropometry-based BF% estimates. Linear regression, Bland-Altman analysis and equivalence testing were performed alongside evaluation of the constant error (CE), total error (TE), se of the estimate (SEE) and coefficient of determination (R2). The major findings were (1) differences between 5C, 4C and 3C models utilising the same body volume (BV) and total body water (TBW) estimates are negligible (CE ≤ 0·2 %; SEE < 0·5 %; TE ≤ 0·5 %; R2 1·00; 95 % limits of agreement (LOA) ≤ 0·9 %); (2) moderate errors from alternate TBW or BV estimates in multi-component models were observed (CE ≤ 1·3 %; SEE ≤ 2·1 %; TE ≤ 2·2 %; R2 ≥ 0·95; 95 % LOA ≤ 4·2 %); (3) small differences between alternate DXA (i.e. tissue v. region) and ADP (i.e. Siri v. Brozek equations) estimates were observed, and both techniques generally performed well (CE < 3·0 %; SEE ≤ 2·3 %; TE ≤ 3·6 %; R2 ≥ 0·88; 95 % LOA ≤ 4·8 %); (4) bioimpedance technologies performed well but exhibited larger individual-level errors (CE < 1·0 %; SEE ≤ 3·1 %; TE ≤ 3·3 %; R2 ≥ 0·94; 95 % LOA ≤ 6·2 %) and (5) anthropometric equations generally performed poorly (CE 0·6- 5·7 %; SEE ≤ 5·1 %; TE ≤ 7·4 %; R2 ≥ 0·67; 95 % LOA ≤ 10·6 %). Collectively, the data presented in this manuscript can aid researchers and clinicians in selecting an appropriate body composition assessment method and understanding the associated errors when compared with a reference multi-component model.
Collapse
|
|
39
|
Tinsley GM, Smith-Ryan AE, Kim Y, Blue MNM, Nickerson BS, Stratton MT, Harty PS. Fat-free mass characteristics vary based on sex, race, and weight status in US adults. Nutr Res 2020; 81:58-70. [PMID: 32882467 DOI: 10.1016/j.nutres.2020.07.002] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 07/06/2020] [Indexed: 11/28/2022]
Abstract
Common body composition estimation techniques necessitate assumptions of uniform fat-free mass (FFM) characteristics, although variation due to sex, race, and body characteristics may occur. National Health and Nutrition Examination Survey data from 1999 to 2004, during which paired dual-energy x-ray absorptiometry (DXA) and bioimpedance spectroscopy assessments were performed, were used to estimate FFM characteristics in a sample of 4619 US adults. Calculated FFM characteristics included the density and water, bone mineral, and residual content of FFM. A rapid 4-component model was also produced using DXA and bioimpedance spectroscopy data. Study variables were compared across sex, race/ethnicity, body mass index (BMI), and age categories using multiple pairwise comparisons. A general linear model was used to estimate body composition after controlling for other variables. Statistical analyses accounted for 6-year sampling weights and complex sampling design of the National Health and Nutrition Examination Survey and were based on 5 multiply imputed datasets. Differences in FFM characteristics across sex, race, and BMI were observed, with notable dissimilarities between men and women for all outcome variables. In racial/ethnic comparisons, non-Hispanic blacks most commonly presented distinct FFM characteristics relative to other groups, including greater FFM density and proportion of bone mineral. Body composition errors between DXA and the 4-component model were significantly influenced by sex, age, race, and BMI. In conclusion, FFM characteristics, which are often assumed in body composition estimation methods, vary due to sex, race/ethnicity, and weight status. The variation of FFM characteristics in diverse populations should be considered when body composition is evaluated.
Collapse
Affiliation(s)
- Grant M Tinsley
- Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University. 3204 Main St, Lubbock, TX 79409, USA.
| | - Abbie E Smith-Ryan
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina. 209 Fetzer Hall, CB# 8700, Chapel Hill, NC 27599, USA
| | - Youngdeok Kim
- Department of Kinesiology & Health Sciences, Virginia Commonwealth University. 1020 W Grace St, Richmond, VA 23284, USA
| | - Malia N M Blue
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina. 209 Fetzer Hall, CB# 8700, Chapel Hill, NC 27599, USA
| | - Brett S Nickerson
- College of Nursing and Health Sciences, Texas A&M International University, 5201 University Blvd, Laredo, TX 78041, USA
| | - Matthew T Stratton
- Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University. 3204 Main St, Lubbock, TX 79409, USA
| | - Patrick S Harty
- Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University. 3204 Main St, Lubbock, TX 79409, USA
| |
Collapse
|
|
40
|
St-Onge MP, Campbell A, Zuraikat F, Cheng B, Shah R, Berger JS, Sampogna RV, Jelic S. Impact of change in bedtime variability on body composition and inflammation: secondary findings from the Go Red for Women Strategically Focused Research Network. Int J Obes (Lond) 2020; 44:1803-1806. [PMID: 32132641 PMCID: PMC7387143 DOI: 10.1038/s41366-020-0555-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 02/06/2020] [Accepted: 02/12/2020] [Indexed: 01/13/2023]
Abstract
Variability in daily sleep patterns is an emerging factor linked to metabolic syndrome. However, whether reducing bedtime variability improves markers of disease risk has not been tested. Here, we assessed whether body composition and inflammation were impacted by changes in bedtime variability over a 6-week period, during which, women were instructed to maintain healthy, habitual sleep (HS) patterns (one arm of a randomized trial). Data were available for 37 women (age 34.9 ± 12.4 years, BMI 24.7 ± 2.9 kg/m2, sleep duration 7.58 ± 0.49 h/night). Body composition and leukocyte platelet aggregates (LPA) were measured at baseline and endpoint using magnetic resonance imaging and flow cytometry, respectively. Sleep data were collected daily using wrist actigraphy. Change in bedtime variability was calculated as the difference in the standard deviation (SD) of bedtimes measured during the 2-week screening period and the 6-week intervention period. Results showed that women who reduced their bedtime variability (n = 29) during the intervention had reductions in total (P < 0.001) and subcutaneous adipose tissue (P < 0.001) relative to women who increased/maintained (n = 8) bedtime variability. Similar effects were observed for LPA levels between women who reduced vs increased/maintained bedtime variability (P = 0.011). Thus, reducing bedtime variability, without changing sleep duration, could improve cardiometabolic health by reducing adiposity and inflammation.
Collapse
Affiliation(s)
- Marie-Pierre St-Onge
- Sleep center of excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA.
| | - Ayanna Campbell
- Sleep center of excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Faris Zuraikat
- Sleep center of excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Bin Cheng
- Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Riddhi Shah
- Sleep center of excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Jeffrey S Berger
- Center for the Prevention of Cardiovascular Disease; Department of Medicine, New York University Langone Health, New York, NY, 10010, USA
| | - Rosemary V Sampogna
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| | - Sanja Jelic
- Sleep center of excellence, Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA
| |
Collapse
|
|
41
|
Lee LW, Liao YS, Lu HK, Hsieh KC, Chi CC. Performance of Bioelectrical Impedance Analysis in the Estimation of Bone Mineral Content in Healthy Children Aged 6-12 Years. J Clin Densitom 2020; 23:411-417. [PMID: 30979543 DOI: 10.1016/j.jocd.2019.03.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/12/2019] [Accepted: 03/12/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Bioelectrical impedance analysis (BIA) is a widely available tool which provides mineral estimate. However, BIA is not currently recognized as a bone mineral measuring method. This study aimed to explore the ability of BIA to predict bone mineral content (BMC) in children, using dual-energy X-ray absorptiometry as a gold standard. METHODS Healthy children aged 6-12 years (n = 176) were recruited for BIA and dual-energy X-ray absorptiometry measurements. Predictive models were generated using basic indices (age, height, weight, waist circumference, hip circumference, etc.) and BIA parameters (minerals, fat mass, and fat free mass). RESULTS The root-mean-square deviation and R2 for the total BMC predictive model were 0.089 kg and 0.926, respectively using height and weight as predictors whereas 0.113 kg and 0.886, respectively using minerals by BIA. The root-mean-square deviation and R2 for the subtotal BMC predictive model were 0.080 kg and 0.935, respectively using height and weight as predictors whereas 0.098 kg and 0.906, respectively using minerals by BIA. The best predictive models included basic indices and BIA parameters as predictors, but they had only slightly better performance over simple models. CONCLUSIONS Mineral content by BIA was good predictor of total and subtotal BMC in healthy children but with similar overall model performance compared to basic indices. More complex models combined all the predictive variables gave better prediction power, but of little improvement to these simple models. The BIA instrument does not appear to be useful in estimating BMC in healthy children as basic indices are more widely available measures but provide comparable performance. Future studies are needed to determine the clinical usefulness of the more complex prediction model in children with disease or children in other subgroups.
Collapse
Affiliation(s)
- Li-Wen Lee
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Chiayi, Taiwan; Department of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Taiwan
| | - Yu-San Liao
- Department of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Taiwan; Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Yunlin, Taiwan
| | - Hsueh-Kuan Lu
- Sport Science Research Center, National Taiwan University of Sport, Taichung, Taiwan
| | - Kuen-Chang Hsieh
- Office of Physical Education and Sport, National Chung Hsing University, Taichung, Taiwan; Research Center, Charder Electronic Co, Ltd, Taichung, Taiwan
| | - Ching-Chi Chi
- Department of Dermatology, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan; College of Medicine, Chang Gung University, Taoyuan, Taiwan.
| |
Collapse
|
|
42
|
Graybeal AJ, Moore ML, Cruz MR, Tinsley GM. Body Composition Assessment in Male and Female Bodybuilders: A 4-Compartment Model Comparison of Dual-Energy X-Ray Absorptiometry and Impedance-Based Devices. J Strength Cond Res 2020; 34:1676-1689. [DOI: 10.1519/jsc.0000000000002831] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
|
|
43
|
Khan S, Xanthakos SA, Hornung L, Arce-Clachar C, Siegel R, Kalkwarf HJ. Relative Accuracy of Bioelectrical Impedance Analysis for Assessing Body Composition in Children With Severe Obesity. J Pediatr Gastroenterol Nutr 2020; 70:e129-e135. [PMID: 32443048 PMCID: PMC7283978 DOI: 10.1097/mpg.0000000000002666] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVES The accuracy of different bioelectrical impedance analysis (BIA) devices for assessing body composition in children with obesity is unclear. We determined the relative accuracy of 2 BIA devices compared to dual x-ray absorptiometry (DXA) in obese and severely obese children. METHODS We measured body composition in a cross-sectional study of 78 obese children by a handheld single frequency tetrapolar BIA device (Omron), a stationary multifrequency octopolar BIA device (InBody 370) and DXA. Intermethod agreement was assessed by intraclass correlations, paired t tests, and Bland-Altman analyses. RESULTS Participants (37% female, age 14.8 ± 2.7 years) had mean (±standard deviation) body mass index of 36.7 ± 7.5 kg/m, body fat percentage of 46.4% ± 5.2%, and appendicular lean mass of 22.5 ± 6.0 kg by DXA. Intraclass correlations with DXA for body fat percentage were 0.39 and 0.87 for single frequency tetrapolar and multifrequency octopolar BIA devices, respectively. The single frequency tetrapolar BIA underestimated body fat percentage by 5.5% ± 2.9% (P < 0.0001). Differences between the multifrequency octopolar BIA and DXA for body fat percentage (-1.1% ± 2.8%) and appendicular lean mass (-0.3 ± 1.4 kg) were small, and 95% limits of agreement were approximately ±5%. CONCLUSIONS BIA machines vary in relative accuracy in measuring body composition in children who are obese and severely obese. The multifrequency octopolar BIA device accurately estimated body fat percentage and appendicular lean mass relative to DXA and has the advantage of point of care performance.
Collapse
Affiliation(s)
- Soofia Khan
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center
| | - Stavra A Xanthakos
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center
- Department of Pediatrics, University of Cincinnati College of Medicine
| | | | - Catalina Arce-Clachar
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center
- Department of Pediatrics, University of Cincinnati College of Medicine
| | - Robert Siegel
- Department of Pediatrics, University of Cincinnati College of Medicine
- Division of Cardiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH
| | - Heidi J Kalkwarf
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center
- Department of Pediatrics, University of Cincinnati College of Medicine
| |
Collapse
|
|
44
|
Nickerson BS, Tinsley GM, Fedewa MV, Esco MR. Fat-free mass characteristics of Hispanic adults: Comparisons with non-Hispanic Caucasians and cadaver reference values. Clin Nutr 2020; 39:3080-3085. [PMID: 32057536 DOI: 10.1016/j.clnu.2020.01.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 01/21/2020] [Accepted: 01/22/2020] [Indexed: 10/25/2022]
Abstract
BACKGROUND A four-compartment (4C) model quantifies fat, water, mineral and residual. As such, 4C models are more accurate than two-compartment (2C) models based off cadaver reference values (RV), which necessitate assumptions regarding fat-free mass (FFM) characteristics. Nonetheless, research has yet to determine whether the FFM characteristics of Hispanics are similar to non-Hispanic Caucasians and RV. AIM The aim of this analysis was to compare the FFM characteristics of Hispanics to non-Hispanic Caucasians and cadaver RV. METHODS Data from 2 separate research centers were pooled to create a sample of 100 and 119 Hispanic males and females (age: 18-54 yrs; BMI: 16.46-42.27 kg/m2), respectively, and 47 and 55 non-Hispanic Caucasian males and females (age: 18-54 yrs; BMI: 16.00-36.67 kg/m2), respectively (n = 331). A 4C model was determined using bioimpedance analysis for hydration, dual energy X-ray absorptiometry for mineral, and air displacement plethysmography for body density (4C-ADP). FFM was calculated via the 4C-ADP and FFM characteristics (i.e., density [DFFM], water [TBW:FFM], bone mineral [Mo:FFM], and residual [R:FFM]) were compared between sexes and ethnicities using a one-way ANOVA and against RV via a one sample t-test. RESULTS In Hispanics, all FFM characteristics significantly differed from cadaver RV (all p < 0.05). In contrast, DFFM and TBW:FFM of non-Hispanic Caucasians were similar to cadaver RV for both sexes (all p > 0.05). Moreover, the R:FFM of non-Hispanic Caucasian females did not differ from cadaver RV (p = 0.403) whereas all other comparisons were significantly different (all p < 0.05). Sex comparisons within Hispanic participants revealed FFM characteristics were similar between males and females other than Mo:FFM (p < 0.001) whereas all FFM characteristics were similar between non-Hispanic Caucasian males and females (all p > 0.05). All of the ethnicity comparisons within males were statistically significant (all p < 0.05). Moreover, ethnicity comparisons within females were statistically significant for all comparisons other than Mo:FFM (p = 0.258). CONCLUSION The observed differences in FFM characteristics of Hispanics as compared to non-Hispanics Caucasians and reference values indicate that allied health professionals should employ appropriate caution when estimating body composition via 2C models in Hispanic populations.
Collapse
Affiliation(s)
- Brett S Nickerson
- College of Nursing and Health Sciences, Texas A&M International University, Laredo, TX, USA.
| | - Grant M Tinsley
- Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, USA
| | - Michael V Fedewa
- Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA
| | - Michael R Esco
- Department of Kinesiology, The University of Alabama, Tuscaloosa, AL, USA
| |
Collapse
|
|
45
|
Nagel E, Hickey M, Teigen L, Kuchnia A, Curran K, Soumekh L, Earthman C, Demerath E, Ramel S. Clinical Application of Body Composition Methods in Premature Infants. JPEN J Parenter Enteral Nutr 2020; 44:785-795. [DOI: 10.1002/jpen.1803] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 01/08/2020] [Accepted: 01/15/2020] [Indexed: 01/25/2023]
Affiliation(s)
- Emily Nagel
- Department of Food Science and NutritionUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| | - Marie Hickey
- Department of PediatricsUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| | - Levi Teigen
- Department of GastroenterologyUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| | - Adam Kuchnia
- Department of Nutritional SciencesUniversity of Wisconsin‐Madison Madison WI USA
| | - Kent Curran
- Department of PediatricsAlbany Medical Center Albany NY USA
| | - Lisa Soumekh
- School of MedicineUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| | | | - Ellen Demerath
- School of Public HealthUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| | - Sara Ramel
- Department of PediatricsUniversity of Minnesota‐Twin Cities Minneapolis MN USA
| |
Collapse
|
|
46
|
Phase angle and bioelectrical impedance vector analysis in the evaluation of body composition in athletes. Clin Nutr 2020; 39:447-454. [PMID: 30850270 DOI: 10.1016/j.clnu.2019.02.016] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 01/21/2019] [Accepted: 02/09/2019] [Indexed: 01/10/2023]
|
|
47
|
Müller MJ, Bosy-Westphal A. Effect of Over- and Underfeeding on Body Composition and Related Metabolic Functions in Humans. Curr Diab Rep 2019; 19:108. [PMID: 31686224 DOI: 10.1007/s11892-019-1221-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
PURPOSE OF REVIEW Methodological limitations of body composition methods limit the validity of changes in body composition that are used to interpret metabolic outcome parameters of weight loss and weight gain. RECENT FINDINGS Direct assessment of energy balance is necessary for the assessment of early weight changes (i.e., within the 1st week of weight change), whereas body composition analysis with a high accuracy and a low minimal detectable change is recommended to assess ongoing changes. The sequence of underfeeding and overfeeding impacts the method inherent assumptions, and the considerable day-to-day and inter-individual variance in body composition changes is a challenge to the precision of methods. Weight loss-associated changes in body composition do not resemble their changes with subsequent hypercaloric re-feeding. Individual body components are related to specific metabolic functions where the structure-function relationships change with changes in energy balance. Analysis of structure-function relationships in response to weight changes needs to address (a) the validity, precision, and different outcome parameters of body composition methods and (b) the variance of results taking into account study protocols and the dynamics of weight changes. As for future studies, repeated measurements of body weight, body composition, and metabolic functions are needed before, during, and after weight changes focusing on the intra- and interindividual variances of weight change rather than on mean data only.
Collapse
Affiliation(s)
- Manfred James Müller
- Institute of Human Nutrition and Food Science, Christian-Albrechts-Universität zu Kiel, Düsternbrooker Weg 17-19, D-24105, Kiel, Germany.
| | - Anja Bosy-Westphal
- Institute of Human Nutrition and Food Science, Christian-Albrechts-Universität zu Kiel, Düsternbrooker Weg 17-19, D-24105, Kiel, Germany
| |
Collapse
|
|
48
|
Muraki R, Hiraoka A, Nagata K, Nakajima K, Oshita T, Arimichi M, Chikazawa G, Yoshitaka H, Sakaguchi T. Novel method for estimating the total blood volume: the importance of adjustment using the ideal body weight and age for the accurate prediction of haemodilution during cardiopulmonary bypass. Interact Cardiovasc Thorac Surg 2019; 27:802-807. [PMID: 29873728 DOI: 10.1093/icvts/ivy173] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Accepted: 04/24/2018] [Indexed: 01/19/2023] Open
Abstract
OBJECTIVES Although total blood volume (TBV) is central to the estimation of the haemodilution rate during cardiopulmonary bypass (CPB), conventional formulas lack sufficient accuracy. The aim of this study was to establish a new formula using ideal body weight (BW) with adjustment for gender or age to estimate TBV for a more accurate prediction of the haemodilution rate during CPB. METHODS A total of 214 consecutive patients who underwent cardiac surgery with CPB were included in this study. TBV was retrospectively estimated using the following formulae: (1) Conventional TBV = actual BW × fixed 70 ml/kg, (2) gender-based modified TBV = ideal BW × 75 ml/kg (male) or 65 ml/kg (female) and (3) age-based modified TBV = ideal BW × 70 ml/kg (<65 years old) or 60 ml/kg (≥65 years old). The relationship between actual and predicted haemodilution rates calculated by these formulas was examined. RESULTS The actual haemodilution rate based on the haematocrit value was 24.4 ± 4.4%. There was no significant correlation between the actual and predicted haemodilution rates obtained by the conventional formula, whereas both modified formulae with the ideal BW showed a significant correlation. Furthermore, the age-based modified formula showed the highest correlation level (r = 0.45, P < 0.001) as well as a strong correlation between the actual and predicted postdilution haematocrit values (y = 0.903x + 3.385, R2 = 0.892). CONCLUSIONS The conventional formula is unable to predict the actual haemodilution rate accurately. Our new formula with a combination of the ideal BW and adjustment for age was shown to be useful for the accurate prediction of the haemodilution rate during CPB.
Collapse
Affiliation(s)
- Ryosuke Muraki
- Department of Clinical Engineering, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Arudo Hiraoka
- Department of Cardiovascular Surgery, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Kazuyuki Nagata
- Department of Clinical Engineering, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Kosuke Nakajima
- Department of Clinical Engineering, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Tomoya Oshita
- Department of Clinical Engineering, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Masahisa Arimichi
- Department of Clinical Engineering, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Genta Chikazawa
- Department of Cardiovascular Surgery, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Hidenori Yoshitaka
- Department of Cardiovascular Surgery, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| | - Taichi Sakaguchi
- Department of Cardiovascular Surgery, The Sakakibara Heart Institute of Okayama, Okayama City, Okayama, Japan
| |
Collapse
|
|
49
|
Smith-Ryan AE, Hirsch KR, Blue MNM, Mock MG, Trexler ET. High-Fat Breakfast Meal Replacement in Overweight and Obesity: Implications on Body Composition, Metabolic Markers, and Satiety. Nutrients 2019; 11:E865. [PMID: 30999596 PMCID: PMC6521626 DOI: 10.3390/nu11040865] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 04/11/2019] [Accepted: 04/12/2019] [Indexed: 11/16/2022] Open
Abstract
The purpose of this paper was to determine the effect of replacing breakfast with a high-fat drink on fat mass (FM), lean mass (LM), percent body fat (%BF), visceral fat (VAT), resting metabolic rate (RMR), fuel utilization (RER), blood lipids and satiety in overweight and obese adults. Healthy adults (n = 42; 21 Females; body mass index (BMI): 32.8 ± 4.6 kg·m-2) were randomized to control (CON; n = 21) or meal replacement (MRP; n = 22) groups. Body composition was measured using a four-compartment model; RMR and RER were assessed from indirect calorimetry. The MRP (70% fat) was consumed once daily for eight weeks. For males, there was no change (p > 0.05) in FM (mean difference (MD) = 0.41 ± 1.19 kg], %BF MD = 0.50 ± 1.09%, LM MD = -0.64 ± 1.79 kg, or VAT MD = -0.31 ± 1.36 cm for MRP versus CON. Similarly, no differences for females for FM MD = -0.73 ± 1.37 kg, %BF MD = -0.57 ± 1.26%, LM MD = 0.31 ± 1.37 kg, or VAT MD: -0.83 ± 1.2 cm. HDL was significantly reduced in the MRP group for females (adjusted mean change: -6.41 ± 4.44 units, p = 0.018). There was no effect on RMR or RER. Satiety increased in the afternoon for MRP (p = 0.021). Despite high fat, no negative impact on lipids resulted; increased satiety may be beneficial for controlling afternoon cravings, but does not affect body composition.
Collapse
Affiliation(s)
- Abbie E Smith-Ryan
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina, Chapel Hill, NC 27599, USA.
- Human Movement Science Curriculum, Department of Allied Health Science, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Katie R Hirsch
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina, Chapel Hill, NC 27599, USA.
- Human Movement Science Curriculum, Department of Allied Health Science, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Malia N M Blue
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina, Chapel Hill, NC 27599, USA.
- Human Movement Science Curriculum, Department of Allied Health Science, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Meredith G Mock
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Eric T Trexler
- Applied Physiology Laboratory, Department of Exercise and Sport Science, The University of North Carolina, Chapel Hill, NC 27599, USA.
- Human Movement Science Curriculum, Department of Allied Health Science, University of North Carolina, Chapel Hill, NC 27599, USA.
| |
Collapse
|
|
50
|
|