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Cattem MVDO, Coelho GMDO, Koury JC. Fat-free mass predictive equation using multifrequency bioelectrical impedance data in adolescent soccer athletes: development and cross-validation. Nutrition 2024; 125:112484. [PMID: 38905911 DOI: 10.1016/j.nut.2024.112484] [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: 02/16/2024] [Revised: 04/04/2024] [Accepted: 05/01/2024] [Indexed: 06/23/2024]
Abstract
OBJECTIVES This study aimed to develop and cross-validate a fat-free mass (FFM) predictive equation using multifrequency bioelectrical impedance analysis (BIA) data in adolescent soccer athletes. METHODS Male adolescent soccer athletes (n = 149; 13-19 y old) were randomly sorted using Excel and independently selected for development group (n = 100) or cross-validation group (n = 49). The FFM reference values were determined using dual-energy X-ray absorptiometry. Single-frequency BIA was used to plot tolerance ellipses. Multifrequency-BIA raw data were used as independent variables in regression models. Student's independent t-test was used to compare development and cross-validation groups. Stepwise multiple regression was used to develop the FFM predictive equation. Bland-Altman plots, Lin's concordance correlation coefficient, according to McBride criteria, precision, accuracy, and standard error of estimate (SEE) were calculated to evaluate the concordance and reliability of estimates. Bioelectrical impedance vector analysis was plotted to assess hydration status. RESULTS No differences (P > 0.05) were observed between development and validation groups in chronological age, anthropometric data, bioelectrical impedance data, and FFM values obtained using dual-energy X-ray absorptiometry. Bioelectrical impedance vector analysis tolerance showed that all participants presented adequate hydration status compared to the reference population. The new FFM predictive equation developed and validated: FFM (kg) = -7.064 + 0.592 × chronological age (y) + 0.554 × weight (kg) + 0.365 × height²/resistance (cm²/Ω), presented R² = 0.95; SEE = 1.76 kg; concordance correlation coefficient = 0.95, accuracy = 0.98, and strength of concordance = 0.99. CONCLUSIONS The present study developed and cross-validated an FFM predictive equation based on multifrequency bioelectrical data providing substantial FFM accuracy for male adolescent soccer athletes.
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Affiliation(s)
| | | | - Josely Correa Koury
- Nutrition Institute, Rio de Janeiro State University, Rio de Janeiro, Brazil.
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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.
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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
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3
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Cattem MVDO, Orsso CE, Gonzalez MC, Koury JC. One-Year Changes in Bioelectrical Impedance Data in Adolescent Athletes. Nutrients 2024; 16:701. [PMID: 38474828 DOI: 10.3390/nu16050701] [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: 01/28/2024] [Revised: 02/25/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Raw bioelectrical impedance (BI) data and vector analysis (BIVA) have been used to evaluate fat-free mass (FFM) cross-sectionally in adolescent athletes; however, there have been no longitudinal studies about it. This study aimed to assess the magnitude of changes in raw BI data (resistance [R], reactance [Xc], and phase angle [PhA]), BIVA, and FFM in adolescent athletes (n = 137, 40% female). BI data were collected using a single-frequency device at baseline and after one year of sports practice. Baseline chronological age categorized the participants (11, 12, or 13 years [y]). In females, Xc/H increased (13 to 14 y, p = 0.04) while R/H decreased in all age groups (p = 0.001). PhA (11 to 12 y, p = 0.048) and FFM (11 to 12 y and 12 to 13 y groups p = 0.001) increased and showed the lowest magnitude of changes in the 13 to 14 y group (p = 0.05). In males, Xc/H decreased (11 to 12 and 12 to 13 y groups, p = 0.001) with a higher magnitude of changes in the 13 to 14 y group (p = 0.004); R/H decreased (p = 0.001); FFM increased in all groups (p = 0.001); however, no magnitude of changes was observed. PhA increased in the 13 to 14 y group (p = 0.004). BIVA showed no differences among ellipse distances in females. In males, a high distance was observed in the 11 to 12 y group. "Time interval" influenced PhA and Xc/H in the female group and R/H and Xc/H in the male group. "Initial age" and "time interval" influenced the increase in PhA in the male group. Raw BI data and BIVA patterns can detect the magnitude of the changes in a sex-dependent manner.
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Affiliation(s)
| | - Camila E Orsso
- Human Nutrition Research Unit, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Maria Cristina Gonzalez
- Post-Graduate Program in Nutrition and Foods, Federal University of Pelotas, Pelotas 96010-610, Brazil
| | - Josely Correa Koury
- Nutrition Institute, Rio de Janeiro State University, Rio de Janeiro 20550-013, Brazil
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DE Almeida-Neto PF, DA Costa RF, DE Macêdo Cesário T, Aidar FJ, DE Matos DG, Dantas PMS, Cabral BGAT. Fat-Free Mass Index for body composition analysis in pediatric sport: a cross-sectional study. J Sports Med Phys Fitness 2024; 64:160-166. [PMID: 37955930 DOI: 10.23736/s0022-4707.23.15377-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
BACKGROUND Analyzing fat free mass (FFM) helps sport professionals during the prescription of sport training for children and adolescents in a sport initiation program. In this way, it is possible to determine fat mass (FM) (FFM subtracted from total body weight) and design interventions to increase FFM and reduce %F, making it possible to maximize performance in relation to the physical demands of sport. However, there is still no reliable anthropometric index to analyze FFM in this population. The aim the present study was to develop the Fat-Free Mass Index (FFMI) for pediatrics of both sexes. METHODS Cross-sectional study with a sample composed of 254 pediatrics (139 males [age: 13.0±2.3] and 115 females [age: 12.5±2.2]), from a sports initiation school. We divided the sample into the groups: 1) development (N.=169); and 2) cross-validation (N.=85). The body composition was analyzed by dual-energy X-ray absorptiometry (DXA), in addition we acquired anthropometric data (height, body weight and hip circumference) for the development of the FFMI - Pediatric (FFMIp). By means of linear regression we tested the predictive power of FFM using DXA as a reference method, then we developed FFMIp and tested its reliability and validity in relation to DXA. RESULTS FFMIp consisted of: -16.679 + (0.615 × body mass (kg)) - (2.601 × sex) + (0.618 × age(years)) - (0.332 × hip(cm)) + (0.278 × stature(cm)), where for sex 0 = male and 1 = female. For the FFM analysis, FFMIp showed no significant difference from DXA (P>0.05). It also showed significant accuracy (Cb>0.960), precision (ρ>0.990) and agreement (CCC>0.960) for both groups (development and cross-validation). CONCLUSIONS Pediatric FFMI proposed by this study proved to be valid for the analysis of fat-free mass in pediatric athletes of sports initiation of both sexes.
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Affiliation(s)
- Paulo F DE Almeida-Neto
- Department of Physical Education, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil -
- Health Sciences Center, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil -
| | - Roberto F DA Costa
- Department of Physical Education, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- Faculty of Health Sciences, Universidad Autónoma de Chile, Santiago, Chile
| | | | - Felipe J Aidar
- Department of Physical Education, Federal University of Sergipe (UFS), São Cristovão, Brazil
- Graduate Program in Master's Level at Department of Physical Education, Federal University of Sergipe (UFS), São Cristovão, Brazil
- Program of Physiological Science, Federal University of Sergipe (UFS), São Cristovão, Brazil
| | - Dihogo G DE Matos
- Cardiovascular and Physiology of Exercise Research Laboratory, Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, MB, Canada
| | - Paulo M S Dantas
- Department of Physical Education, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- Faculty of Health Sciences, Universidad Autónoma de Chile, Santiago, Chile
| | - Breno G A T Cabral
- Department of Physical Education, Federal University of Rio Grande do Norte (UFRN), Natal, Brazil
- Faculty of Health Sciences, Universidad Autónoma de Chile, Santiago, Chile
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5
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Silva AM, Campa F, Stagi S, Gobbo LA, Buffa R, Toselli S, Silva DAS, Gonçalves EM, Langer RD, Guerra-Júnior G, Machado DRL, Kondo E, Sagayama H, Omi N, Yamada Y, Yoshida T, Fukuda W, Gonzalez MC, Orlandi SP, Koury JC, Moro T, Paoli A, Kruger S, Schutte AE, Andreolli A, Earthman CP, Fuchs-Tarlovsky V, Irurtia A, Castizo-Olier J, Mascherini G, Petri C, Busert LK, Cortina-Borja M, Bailey J, Tausanovitch Z, Lelijveld N, Ghazzawi HA, Amawi AT, Tinsley G, Kangas ST, Salpéteur C, Vázquez-Vázquez A, Fewtrell M, Ceolin C, Sergi G, Ward LC, Heitmann BL, da Costa RF, Vicente-Rodriguez G, Cremasco MM, Moroni A, Shepherd J, Moon J, Knaan T, Müller MJ, Braun W, García-Almeida JM, Palmeira AL, Santos I, Larsen SC, Zhang X, Speakman JR, Plank LD, Swinburn BA, Ssensamba JT, Shiose K, Cyrino ES, Bosy-Westphal A, Heymsfield SB, Lukaski H, Sardinha LB, Wells JC, Marini E. The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data. Eur J Clin Nutr 2023; 77:1143-1150. [PMID: 37532867 DOI: 10.1038/s41430-023-01310-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 07/10/2023] [Accepted: 07/12/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND Bioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians' offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the 'BIA International Database' project and encourage researchers to join the consortium. METHODS The Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants. CONCLUSION The BIA International Database represents a key resource for research on body composition.
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Affiliation(s)
- Analiza M Silva
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002, Lisbon, Portugal.
| | - Francesco Campa
- Department of Biomedical Science, University of Padova, 35100, Padova, Italy
| | - Silvia Stagi
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, 09042, Cagliari, Italy
| | - Luís A Gobbo
- Skeletal Muscle Assessment Laboratory, Physical Education Department, School of Technology and Science, São Paulo State University, Presidente Prudente, 19060-900, Brazil
| | - Roberto Buffa
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, 09042, Cagliari, Italy
| | - Stefania Toselli
- Department for Life Quality Studies, University of Bologna, 47921, Rimini, Italy
| | - Diego Augusto Santos Silva
- Research Center of Kinanthropometry and Human Performance, Sports Center, Universidade Federal de Santa Catarina, Florianópolis, Brazil
| | - Ezequiel M Gonçalves
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, 13083-887, Brazil
| | - Raquel D Langer
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, 13083-887, Brazil
| | - Gil Guerra-Júnior
- Growth and Development Laboratory, Center for Investigation in Pediatrics (CIPED), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, 13083-887, Brazil
| | - Dalmo R L Machado
- Laboratory of Kinanthropometry and Human Performance, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, 05508-030, São Paulo, Brazil
| | - Emi Kondo
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, 305-8574, Japan
| | - Hiroyuki Sagayama
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, 305-8574, Japan
| | - Naomi Omi
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, 305-8574, Japan
| | - Yosuke Yamada
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 566-0002, Japan
| | - Tsukasa Yoshida
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 566-0002, Japan
| | - Wataru Fukuda
- Yokohama Sports Medical Center, Yokohama Sport Association, Kanagawa, 222-0036, Japan
| | - Maria Cristina Gonzalez
- Postgraduate Program in Nutrition and Food, Federal University of Pelotas, 96010-610 Pelotas, Brazil
| | - Silvana P Orlandi
- Nutrition Department, Federal University of Pelotas, 96010-610, Pelotas, Brazil
| | - Josely C Koury
- Nutrition Institute, State University of Rio de Janeiro, 20550-013, Rio de Janeiro, Brazil
| | - Tatiana Moro
- Department of Biomedical Science, University of Padova, 35100, Padova, Italy
| | - Antonio Paoli
- Department of Biomedical Science, University of Padova, 35100, Padova, Italy
| | - Salome Kruger
- Centre of Excellence for Nutrition, North-West University, Potchefstroom, 2520, South Africa
| | - Aletta E Schutte
- School of Population Health, University of New South Wales, The George Institute for Global Health, Sydney, NSW, Australia
| | | | | | | | - Alfredo Irurtia
- National Institute of Physical Education of Catalonia (INEFC), University of Barcelona (UB), Barcelona, Spain
| | - Jorge Castizo-Olier
- School of Health Sciences, TecnoCampus, Pompeu Fabra University, Barcelona, Spain
| | - Gabriele Mascherini
- Department of Experimental and Clinical Medicine, University of Florence, Firenze, Italy
| | - Cristian Petri
- Department of Sports and Computer Science, Section of Physical Education and Sports, Universidad Pablo de Olavide, Seville, Spain
| | - Laura K Busert
- Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Mario Cortina-Borja
- Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | | | | | | | - Hadeel Ali Ghazzawi
- Department of Nutrition and Food Technology, School of Agriculture, The University of Jordan, Amman, Jordan
| | - Adam Tawfiq Amawi
- Department of Physical and Health Education, Faculty of Educational Sciences, Al-Ahliyya Amman University, Al-Salt, Jordan
| | - Grant Tinsley
- Energy Balance & Body Composition Laboratory, Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX, 79409, USA
| | - Suvi T Kangas
- International Rescue Committee, New York, NY, 10168, USA
| | - Cécile Salpéteur
- Department of Expertise and Advocacy, Action contre la Faim, 93358, Montreuil, France
| | - Adriana Vázquez-Vázquez
- Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Mary Fewtrell
- Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Chiara Ceolin
- Department of Medicine (DIMED), Geriatrics Division, University of Padova, Padova, 35128, Italy
| | - Giuseppe Sergi
- Department of Medicine (DIMED), Geriatrics Division, University of Padova, Padova, 35128, Italy
| | - Leigh C Ward
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Berit L Heitmann
- Research Unit for Dietary Studies, The Parker Institute, Frederiksberg and Bispebjerg Hospital, Copenhagen, Denmark
- Section for general Practice, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Roberto Fernandes da Costa
- Department of Physical Education, Research Group in Physical Activity and Health, Federal University of Rio Grande do Norte, Natal, Brazil
| | - German Vicente-Rodriguez
- Faculty of Health and Sport Science FCSD, Department of Physiatry and Nursing, University of Zaragoza, 50009, Zaragoza, Spain
| | - Margherita Micheletti Cremasco
- Laboratory of Anthropology, Anthropometry and Ergonomics, Department of Life Sciences and Systems Biology, University of Torino, 10123, Torino, Italy
| | - Alessia Moroni
- Laboratory of Anthropology, Anthropometry and Ergonomics, Department of Life Sciences and Systems Biology, University of Torino, 10123, Torino, Italy
| | - John Shepherd
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Jordan Moon
- United States Sports Academy, Daphne, AL, 36526, USA
| | - Tzachi Knaan
- Weight Management, Metabolism & Sports Nutrition Clinic, Metabolic Lab, Tel-Aviv, Tel Aviv-Yafo, Israel
| | - Manfred J Müller
- Department of Human Nutrition, Institute of Human Nutrition and Food Sciences, Christian-Albrechts University, 24105, Kiel, Germany
| | - Wiebke Braun
- Department of Human Nutrition, Institute of Human Nutrition and Food Sciences, Christian-Albrechts University, 24105, Kiel, Germany
| | - José M García-Almeida
- Department of Endocrinology and Nutrition, Virgen de la Victoria Hospital, Malaga University, 29010, Malaga, Spain
| | | | - Inês Santos
- Laboratório de Nutrição, Faculdade de Medicina, Centro Académico de Medicina de Lisboa, Universidade de Lisboa, Lisboa, Portugal
| | - Sofus C Larsen
- Research Unit for Dietary Studies at the Parker Institute, Bispebjerg and Frederiksberg Hospital, The Capital Region, Frederiksberg, Denmark
- The Research Unit for General Practice and Section of General Practice, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Xueying Zhang
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - John R Speakman
- Shenzhen Key Laboratory of Metabolic Health, Center for Energy Metabolism and Reproduction, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | - Lindsay D Plank
- Department of Surgery, University of Auckland, Auckland, New Zealand
| | - Boyd A Swinburn
- School of Population Health, University of Auckland, Auckland, New Zealand
| | - Jude Thaddeus Ssensamba
- Center for Innovations in Health Africa (CIHA Uganda), Kampala, Uganda
- Makerere University Walter Reed Project, Kampala, Uganda
| | - Keisuke Shiose
- Faculty of Education, University of Miyazaki, Miyazaki, Japan
| | - Edilson S Cyrino
- Metabolism, Nutrition, and Exercise Laboratory. Physical Education and Sport Center, State University of Londrina, Rod. Celso Garcia Cid, Km 380, 86057-970, Londrina-PR, Brazil
| | - Anja Bosy-Westphal
- Department of Human Nutrition, Institute of Human Nutrition and Food Sciences, Christian-Albrechts University, 24105, Kiel, Germany
| | | | - Henry Lukaski
- Department of Kinesiology and Public Health Education, Hyslop Sports Center, University of North Dakota Grand Forks, Grand Forks, ND, 58202, USA
| | - Luís B Sardinha
- Exercise and Health Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002, Lisbon, Portugal
| | - Jonathan C Wells
- Population, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Elisabetta Marini
- Department of Life and Environmental Sciences, University of Cagliari, Cittadella Universitaria, Monserrato, 09042, Cagliari, Italy
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6
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Reis-Silva A, Coelho-Oliveira AC, Moura-Fernandes MC, Bruno Bessa MO, Batouli-Santos D, Bernardo-Filho M, de Sá Caputo DDC. Evidence of whole-body vibration exercises on body composition changes in older individuals: a systematic review and meta-analysis. Front Physiol 2023; 14:1202613. [PMID: 38028790 PMCID: PMC10652794 DOI: 10.3389/fphys.2023.1202613] [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: 04/08/2023] [Accepted: 10/03/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction: The aging process is associated with changes in body composition, including fat gain and skeletal muscle loss from middle age onward. Moreover, increased risk of functional decline and the development of chronic diseases are also related to aging. Objective: This systematic review and meta-analysis aimed to evaluate the effects of whole-body vibration exercise (WBVE), as a physical exercise, on body composition in people over 60 years of age. Methods: Searches were performed on PubMed, Scopus, Web of Science, and Embase. Only randomized clinical trials evaluating the effects of WBVE on body composition in older individuals were considered. The methodological quality of the studies involved was assessed using the Physiotherapy Evidence Database (PEDro) scale, recommendations from the Cochrane Collaboration were used to assess risk of bias, and quality of evidence was assessed using the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology. RevMan 5.4 was used to calculate standardized mean differences and confidence intervals of 95% (CIs). Results: Eight studies were included in this review with a mean methodological quality score of 7.5, which is considered high quality on the PEDro scale. The included studies suggest that more robust research with protocols and well-designed comparison groups is required to better assess changes in the body composition of older individuals through WBVE. Quantitative results were calculated, with differences in weighted means, differences in standardized means, and 95% confidence intervals (CIs). Conclusion: WBVE evaluated by the studies included in this review did not demonstrate improvements in body composition, and no significant effect of WBVE was found on fat mass with standardized differences (SD = -1.92; 95% CI: -4.81 to -0.98; p = 0.19), lean mass with standardized mean differences (SMD = 0.06 CI 95% [-0.21; -0.33]; p = 0.67), or skeletal muscle mass with standardized differences (SD = 0.10; CI 95% [-1.62; 1.83]; p = 0.91). Therefore, to date, there is lack of adequate evidence to state that WBVE can benefit the body composition of men and women over 60 years of age. However, further studies are required to better understand the physiological impacts of WBVE on body composition. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/#myprosperoCRD42021248871, identifier CRD42021248871.
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Affiliation(s)
- Aline Reis-Silva
- Programa de Pós-Graduação em Ciências Médicas, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Ana Carolina Coelho-Oliveira
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Programa de Pós-Graduação em Fisiopatologia Clínica e Experimental, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Márcia Cristina Moura-Fernandes
- Programa de Pós-Graduação em Ciências Médicas, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Monteiro-Oliveira Bruno Bessa
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Programa de Pós-Graduação em Fisiopatologia Clínica e Experimental, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Daniel Batouli-Santos
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
- Programa de Pós-Graduação em Fisiopatologia Clínica e Experimental, Faculdade de Ciências Médicas, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Mario Bernardo-Filho
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Danúbia da Cunha de Sá Caputo
- Laboratório de Vibrações Mecânicas e Práticas Integrativas, Instituto de Biologia Roberto Alcântara Gomes e Policlínica Universitária Piquet Carneiro, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
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Felipe de Oliveira Guedes F, Matias de Sousa I, Cunha de Medeiros GO, Gonzalez MC, Trussardi Fayh AP. Is there a difference in the parameters of the bioelectrical impedance obtained from devices from different manufacturers? A cross-sectional study in hospitalized cancer patients. Clin Nutr ESPEN 2023; 56:120-126. [PMID: 37344060 DOI: 10.1016/j.clnesp.2023.05.010] [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: 11/14/2022] [Revised: 05/02/2023] [Accepted: 05/15/2023] [Indexed: 06/23/2023]
Abstract
BACKGROUND Cancer is a disease with high and increasing incidence rates in the world and its course tends to harm the body composition. Monitoring these body changes is very important. Therefore, it is essential to have reliable, accessible, and practical methods for evaluating body compartments. This study aims to evaluate the correlation and agreement of results for the bioelectrical impedance analysis (BIA) obtained from devices from different manufacturers. METHODS This is a single-center cross-sectional study including hospitalized patients with cancer. Two devices from different brands used for obtaining the BIA were used; both with a tetrapolar model and a single frequency (50 kHz). The results were evaluated for resistance (R) and reactance (Xc) and used to calculate the phase angle (PhA) and fat-free mass (FFM) indicators. Pearson and Spearman correlation tests and Bland-Altman plots were performed, with results expressed as bias and limits of agreement at 95% confidence intervals (95%CI). RESULTS We have included 116 patients, with a mean age of 60.8 ± 14.8, 51.7% were women. We have found very strong correlations between the measurements of R (rho = 0.971) and FFM (r = 0.979), and strong correlations for Xc (rho = 0.784) and PhA (rho = 0.768). However, the measurements did not agree between the methods. CONCLUSIONS Commercial brands of devices used for the BIA influence the results generated, a factor that must be considered when choosing the most appropriate method for this analysis.
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Affiliation(s)
| | - Iasmin Matias de Sousa
- Postgraduate Program in Health Sciences, Federal University of Rio Grande Do Norte, Natal, RN, Brazil
| | | | | | - Ana Paula Trussardi Fayh
- Postgraduate Program in Health Sciences, Federal University of Rio Grande Do Norte, Natal, RN, Brazil; PesqClin Lab, Onofre Lopes University Hospital, Brazilian Company of Hospital Services (EBSERH), Federal University of Rio Grande Do Norte, Natal, Brazil; Postgraduate Program in Nutrition, Health Sciences Center, Federal University of Rio Grande Do Norte, Natal, RN, Brazil.
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de Almeida-Neto PF, Cesário TDM, Fernandes da Costa R, de Matos DG, Aidar FJ, Dantas PMS, Cabral BGDAT. Validity of the relative fat mass pediatric index (RFMp) for the analysis of body composition in physically active youths at different stages of biological maturation. J Hum Nutr Diet 2023. [PMID: 36840429 DOI: 10.1111/jhn.13161] [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: 11/05/2022] [Accepted: 02/13/2023] [Indexed: 02/26/2023]
Abstract
BACKGROUND The paediatric relative fat mass (RFMp) index was valid for analysis of percent body fat (BF%). However, the validation did not consider biological maturation (BM) stages. The present study aimed to verify the validity of the RFMp index in the estimation of BF% in children and adolescents of both sexes at different stages of BM. METHODS A cross-sectional study was conducted with a sample of 146 young (males: 64.5%. females: 35.5%. age: 13.0 ± 2.2 years) practising sports modalities. We tested the validity of four RFMp equations (1: for boys aged 8-14 years; 2: for girls aged 8-14 years; 3: for both sexes aged 8-14 years; and 4: for both sexes aged 15-19 years) to analyse BF% using dual-energy X-ray absorptiometry as a reference method. BM was analysed by peak height velocity (PHV). Thus, we created subgroups by BM stage (pre-PHV, circum-PHV and post-PHV). RESULTS Analyses of agreement between methods showed that only the RFMp-3 equation was reliable to analyse BF% in subjects of both sexes aged 8-14 years at the circum-PHV BM stage (proportion bias 95% confidence interval = -0.3 to 0.5, p = 0.7. concordance correlation coefficient = 0.3; validity = 0.9). CONCLUSIONS The RFMp equation developed for the paediatric population of both sexes aged 8-14 years was valid for predicting BF% in children and adolescents of both sexes at the Circum-PHV stage of the BM.
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Affiliation(s)
- Paulo Francisco de Almeida-Neto
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Physical Education, Federal University of Rio Grande do Norte, Natal, Brazil
| | | | | | - Dihogo Gama de Matos
- Cardiovascular & Physiology of Exercise Research Laboratory, Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, MB, Canada
| | - Felipe J Aidar
- Department of Physical Education, Federal University of Sergipe - UFS, São Cristovão, Brazil.,Graduate Program in Master's Level at Department of Physical Education, Federal University of Sergipe - UFS, São Cristovão, Brazil.,Program of Physiological Science, Federal University of Sergipe - UFS, São Cristovão, Brazil
| | - Paulo Moreira Silva Dantas
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Physical Education, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Breno Guilherme de Araújo Tinôco Cabral
- Health Sciences Center, Federal University of Rio Grande do Norte, Natal, Brazil.,Department of Physical Education, Federal University of Rio Grande do Norte, Natal, Brazil
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9
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Triponderal mass index is as strong as body mass index in the determination of obesity and adiposity. Nutrition 2023; 105:111846. [PMID: 36265325 DOI: 10.1016/j.nut.2022.111846] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/18/2022] [Accepted: 08/31/2022] [Indexed: 11/21/2022]
Abstract
OBJECTIVE In determining obesity and body adiposity, triponderal mass index (TMI) is as strong an anthropometric measurement as body mass index (BMI). The aim of this study was to develop TMI reference values for Turkish children and adolescents and compare TMI with BMI according to body adiposity and obesity indices. METHODS Data from the DAMTCA-II (Determination of Anthropometric Measurements of Turkish Children and Adolescents II) study were used in this cross-sectional study. Data from 4330 children (1931 boys, 2399 girls) ages 6 to 17 y were evaluated, and the TMI percentile values were produced. The predictive power of TMI and BMI for obesity and overweight were done for waist circumference, waist/height ratio, body fat percentage, and upper arm fat area, which are different parameters used to determine body adiposity. RESULTS The 3rd, 5th, 10th, 25th, 50th, 75th, 85th, 90th, 95th, and 97th TMI percentiles and mean values were calculated for all children's age and sex. TMI cutoff values were calculated by receiver operating characteristic analysis regarding waist/height ratio 0.5, waist circumference ≥90 percentile, arm fat area ≥85 percentile, and body fat percentage ≥85. TMI and BMI area under the curve values were similar for each of these four measurements. TMI was as robust an index as BMI in demonstrating obesity and adiposity for all age groups in boys and girls. It was concluded that the values >90th percentile (median 15.8 kg/m3) in girls aged ≤10 y, 95th percentile (median 16.2 kg/m3) in girls aged >10 y, >85th percentile (median 14.9 kg/m3) in boys aged ≤12 y and 75th percentile (median value 14.5 kg/m3) in boys aged >12 y are critical values for TMI when evaluating adiposity and obesity. CONCLUSIONS We considered that TMI is as effective as BMI in terms of waist/height ratio, waist circumference, arm fat area, and body fat percentage in determining overweight and obesity in children. The ages at which TMI showed distinct variation were determined for both sexes.
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Bou Khalil R, Sultan A, Seneque M, Richa S, Lefebvre P, Renard E, Courtet P, Maimoun L, Guillaume S. Clinical Correlates of Measured and Predicted Resting Energy Expenditure in Patients with Anorexia Nervosa: A Retrospective Cohort Study. Nutrients 2022; 14:2727. [PMID: 35807906 PMCID: PMC9269154 DOI: 10.3390/nu14132727] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/24/2022] [Accepted: 06/27/2022] [Indexed: 11/24/2022] Open
Abstract
Resting energy expenditure (REE; i.e., the calorie amount required for 24 h during a non-active period) is an important parameter in nutritional rehabilitation of patients with anorexia nervosa (AN). This study determined whether age, body mass index, AN duration/subtype/specific symptoms/clinical severity, cognitive function alterations, and psychiatric comorbidities influenced REE or the difference between the calculated and estimated REE. Patients with AN who were followed at a daycare treatment facility between May 2017 and January 2020 (n = 138) underwent a complete assessment that included the MINI, Eating Disorder Examination Questionnaire, d2 test of attention, body fat composition by bioelectrical impedance analysis (BIA) and REE measurement by indirect calorimetry (REEIC). AN subtype (N = 66 for restrictive subtype and N = 69 for non-restrictive subtype; p = 0.005), free-fat mass (<0.001), and fat mass (<0.001) were associated with REEIC. Age (p < 0.001), height (p = 0.003), and AN duration (N = 46 for <3 years and N = 82 for ≥3 years; p = 0.012) were associated with the difference between estimated REE (using the Schebendach equation) and measured REEIC. Therefore, the Schebendach equation was adjusted differently in the two patients’ subgroups (AN duration ≤ or >3 years). Overall, REE was higher in patients with restrictive than non-restrictive AN. In the absence of BIA measures, REE-estimating equations should take into account AN duration.
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Affiliation(s)
- Rami Bou Khalil
- Department of Psychiatry, Saint Joseph University-Hôtel Dieu de France Hospital, Mar Mikhael, Beirut 17-5208, Lebanon;
- PSNREC, University of Montpellier, INSERM, CHU de Montpellier, 34295 Montpellier, France; (M.S.); (P.C.); (S.G.)
- UMR CNRS 5203, Institute of Functional Genomics, University of Montpellier, INSERM U1191, 34295 Montpellier, France;
- Department of Psychiatric Emergency and Acute Care, Lapeyronie Hospital, CHRU, 34295 Montpellier, France
| | - Ariane Sultan
- UMR CNRS 5203, Institute of Functional Genomics, University of Montpellier, INSERM U1191, 34295 Montpellier, France;
- Department of Psychiatric Emergency and Acute Care, Lapeyronie Hospital, CHRU, 34295 Montpellier, France
| | - Maude Seneque
- PSNREC, University of Montpellier, INSERM, CHU de Montpellier, 34295 Montpellier, France; (M.S.); (P.C.); (S.G.)
- Department of Psychiatric Emergency and Acute Care, Lapeyronie Hospital, CHRU, 34295 Montpellier, France
| | - Sami Richa
- Department of Psychiatry, Saint Joseph University-Hôtel Dieu de France Hospital, Mar Mikhael, Beirut 17-5208, Lebanon;
| | - Patrick Lefebvre
- Department of Endocrinology, Diabetes and Nutrition, CHRU, 34295 Montpellier, France; (P.L.); (E.R.); (L.M.)
| | - Eric Renard
- Department of Endocrinology, Diabetes and Nutrition, CHRU, 34295 Montpellier, France; (P.L.); (E.R.); (L.M.)
- Institute of Functional Genomics, University of Montpellier, INSERM, CNRS, 34295 Montpellier, France
| | - Philippe Courtet
- PSNREC, University of Montpellier, INSERM, CHU de Montpellier, 34295 Montpellier, France; (M.S.); (P.C.); (S.G.)
- UMR CNRS 5203, Institute of Functional Genomics, University of Montpellier, INSERM U1191, 34295 Montpellier, France;
- Department of Psychiatric Emergency and Acute Care, Lapeyronie Hospital, CHRU, 34295 Montpellier, France
| | - Laurent Maimoun
- Department of Endocrinology, Diabetes and Nutrition, CHRU, 34295 Montpellier, France; (P.L.); (E.R.); (L.M.)
- Département de Médecine Nucléaire, Hôpital Lapeyronie, Centre Hospitalier Régional Universitaire (CHRU) Montpellier, 34295 Montpellier, France
| | - Sebastien Guillaume
- PSNREC, University of Montpellier, INSERM, CHU de Montpellier, 34295 Montpellier, France; (M.S.); (P.C.); (S.G.)
- UMR CNRS 5203, Institute of Functional Genomics, University of Montpellier, INSERM U1191, 34295 Montpellier, France;
- Department of Psychiatric Emergency and Acute Care, Lapeyronie Hospital, CHRU, 34295 Montpellier, France
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