Tiago R Silva, Filipe Jesus, Rui Poínhos, Luís B Sardinha, Vitor Hugo Teixeira, Steven B Heymsfield, Analiza M Silva
{"title":"利用双能x射线吸收仪估算运动员体体积的新型对比分析和方程开发。","authors":"Tiago R Silva, Filipe Jesus, Rui Poínhos, Luís B Sardinha, Vitor Hugo Teixeira, Steven B Heymsfield, Analiza M Silva","doi":"10.1038/s41430-025-01594-1","DOIUrl":null,"url":null,"abstract":"<p><strong>Background/objectives: </strong>Dual-energy x-ray absorptiometry (DXA) has been suggested as an alternative method for estimating body volume (BV), a component of the reference four-compartment body composition model. This study reports the development and validation of DXA-BV<sub>Silva</sub>, a novel DXA-derived BV equation. An additional aim was to develop an estimate of lean soft tissue density (D<sub>LST</sub>), a key variable in the theory-based approach, by estimating total body protein with a six-compartment model.</p><p><strong>Methods: </strong>A sample of 332 athletes (36.7% females) from several sports were randomly assigned to either the development (n = 232) or cross-validation group (n = 100). DXA-BV<sub>Silva</sub> was developed via linear regression of DXA-measured fat, lean soft tissue, and bone mineral mass against BV measured with air displacement plethysmography (ADP). A D<sub>LST</sub> estimate of 1.064 kg/L (SD = 0.006) was obtained from a subset of the development sample comprising 201 athletes (36.3% females) with available measurements of total-body water by deuterium dilution, bone mineral by DXA and BV by ADP, enabling total-body protein determination from a six-compartment model.</p><p><strong>Results: </strong>DXA-BV<sub>Silva</sub> provided the closest BV estimation (mean difference = 0.05 L, SD = 0.46 L; ES [95% CI] = 0.11 [-0.08; 0.31]) and the 95% limits of agreement (-0.86 to 0.96 L) were narrower than existing empirical equations.</p><p><strong>Conclusion: </strong>We conducted the first comparative analysis of both empirical and theoretical BV estimation methods using DXA, demonstrating the validity of DXA-BV<sub>Silva</sub> for BV estimation in athletes, presenting a robust alternative to ADP, with potential applications in multicomponent body composition models.</p>","PeriodicalId":11927,"journal":{"name":"European Journal of Clinical Nutrition","volume":" ","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel comparative analysis and equation development for body volume estimation using dual-energy x-ray absorptiometry in athletes.\",\"authors\":\"Tiago R Silva, Filipe Jesus, Rui Poínhos, Luís B Sardinha, Vitor Hugo Teixeira, Steven B Heymsfield, Analiza M Silva\",\"doi\":\"10.1038/s41430-025-01594-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background/objectives: </strong>Dual-energy x-ray absorptiometry (DXA) has been suggested as an alternative method for estimating body volume (BV), a component of the reference four-compartment body composition model. This study reports the development and validation of DXA-BV<sub>Silva</sub>, a novel DXA-derived BV equation. An additional aim was to develop an estimate of lean soft tissue density (D<sub>LST</sub>), a key variable in the theory-based approach, by estimating total body protein with a six-compartment model.</p><p><strong>Methods: </strong>A sample of 332 athletes (36.7% females) from several sports were randomly assigned to either the development (n = 232) or cross-validation group (n = 100). DXA-BV<sub>Silva</sub> was developed via linear regression of DXA-measured fat, lean soft tissue, and bone mineral mass against BV measured with air displacement plethysmography (ADP). A D<sub>LST</sub> estimate of 1.064 kg/L (SD = 0.006) was obtained from a subset of the development sample comprising 201 athletes (36.3% females) with available measurements of total-body water by deuterium dilution, bone mineral by DXA and BV by ADP, enabling total-body protein determination from a six-compartment model.</p><p><strong>Results: </strong>DXA-BV<sub>Silva</sub> provided the closest BV estimation (mean difference = 0.05 L, SD = 0.46 L; ES [95% CI] = 0.11 [-0.08; 0.31]) and the 95% limits of agreement (-0.86 to 0.96 L) were narrower than existing empirical equations.</p><p><strong>Conclusion: </strong>We conducted the first comparative analysis of both empirical and theoretical BV estimation methods using DXA, demonstrating the validity of DXA-BV<sub>Silva</sub> for BV estimation in athletes, presenting a robust alternative to ADP, with potential applications in multicomponent body composition models.</p>\",\"PeriodicalId\":11927,\"journal\":{\"name\":\"European Journal of Clinical Nutrition\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Journal of Clinical Nutrition\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1038/s41430-025-01594-1\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NUTRITION & DIETETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Clinical Nutrition","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41430-025-01594-1","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NUTRITION & DIETETICS","Score":null,"Total":0}
Novel comparative analysis and equation development for body volume estimation using dual-energy x-ray absorptiometry in athletes.
Background/objectives: Dual-energy x-ray absorptiometry (DXA) has been suggested as an alternative method for estimating body volume (BV), a component of the reference four-compartment body composition model. This study reports the development and validation of DXA-BVSilva, a novel DXA-derived BV equation. An additional aim was to develop an estimate of lean soft tissue density (DLST), a key variable in the theory-based approach, by estimating total body protein with a six-compartment model.
Methods: A sample of 332 athletes (36.7% females) from several sports were randomly assigned to either the development (n = 232) or cross-validation group (n = 100). DXA-BVSilva was developed via linear regression of DXA-measured fat, lean soft tissue, and bone mineral mass against BV measured with air displacement plethysmography (ADP). A DLST estimate of 1.064 kg/L (SD = 0.006) was obtained from a subset of the development sample comprising 201 athletes (36.3% females) with available measurements of total-body water by deuterium dilution, bone mineral by DXA and BV by ADP, enabling total-body protein determination from a six-compartment model.
Results: DXA-BVSilva provided the closest BV estimation (mean difference = 0.05 L, SD = 0.46 L; ES [95% CI] = 0.11 [-0.08; 0.31]) and the 95% limits of agreement (-0.86 to 0.96 L) were narrower than existing empirical equations.
Conclusion: We conducted the first comparative analysis of both empirical and theoretical BV estimation methods using DXA, demonstrating the validity of DXA-BVSilva for BV estimation in athletes, presenting a robust alternative to ADP, with potential applications in multicomponent body composition models.
期刊介绍:
The European Journal of Clinical Nutrition (EJCN) is an international, peer-reviewed journal covering all aspects of human and clinical nutrition. The journal welcomes original research, reviews, case reports and brief communications based on clinical, metabolic and epidemiological studies that describe methodologies, mechanisms, associations and benefits of nutritional interventions for clinical disease and health promotion.
Topics of interest include but are not limited to:
Nutrition and Health (including climate and ecological aspects)
Metabolism & Metabolomics
Genomics and personalized strategies in nutrition
Nutrition during the early life cycle
Health issues and nutrition in the elderly
Phenotyping in clinical nutrition
Nutrition in acute and chronic diseases
The double burden of ''malnutrition'': Under-nutrition and Obesity
Prevention of Non Communicable Diseases (NCD)