{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T19:15:08Z","timestamp":1768763708725,"version":"3.49.0"},"reference-count":38,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T00:00:00Z","timestamp":1720396800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"<jats:p>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\u2009\u00b1\u20091.5\u2009years; body mass index: 21.2\u2009\u00b1\u20092.7\u2009kg\/m<jats:sup>2<\/jats:sup>) participated. A 6-compartment model was used as the reference method (TBPro<jats:sub>Reference<\/jats:sub>) 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\u2009=\u2009lean-soft mass (LSM) \u2212 HF<jats:sub>FFM<\/jats:sub> \u00d7 fat-free mass (FFM) \u2212 Ms. \u2212 G, where LSM and FFM were assessed using DXA, HF<jats:sub>FFM<\/jats:sub> is the hydration fraction of the FFM using measured TBW or assumed TBW (adult fraction of 0.732; Lohman\u2019s constants or mean observed HF<jats:sub>FFM<\/jats:sub>), Ms. is soft tissue minerals (Ms\u2009=\u20090.0129 \u00d7 HF<jats:sub>FFM<\/jats:sub> \u00d7 FFM), and G is glycogen calculated as 0.044 \u00d7 (LSM \u2212 HF<jats:sub>FFM<\/jats:sub> \u00d7 FFM \u2212 Ms). The maturation level was determined by self-assessment. TBPro obtained from DXA using the assumed HF<jats:sub>FFM<\/jats:sub> explained 73% to 77% of the variance compared to TBPro<jats:sub>Reference.<\/jats:sub> Meanwhile, using the mean values of measured HF<jats:sub>FFM<\/jats:sub>, 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 HF<jats:sub>FFM<\/jats:sub> (boys for 66.9% and girls for 70%) compared to an assumed HF<jats:sub>FFM<\/jats:sub> (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 HF<jats:sub>FFM<\/jats:sub> 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.<\/jats:p>","DOI":"10.3389\/fnut.2024.1439208","type":"journal-article","created":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T16:24:16Z","timestamp":1720455856000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["The usefulness of total body protein mass models for adolescent athletes"],"prefix":"10.3389","volume":"11","author":[{"given":"Analiza M.","family":"Silva","sequence":"first","affiliation":[]},{"given":"Francesco","family":"Campa","sequence":"additional","affiliation":[]},{"given":"Lu\u00eds B.","family":"Sardinha","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2024,7,8]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1032","DOI":"10.1093\/jn\/136.4.1032","article-title":"Total body protein mass: validation of total body potassium prediction model in children and adolescents","volume":"136","author":"Wang","year":"2006","journal-title":"J Nutr"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1038\/s41430-018-0321-9","article-title":"Structural and functional body components in athletic health and performance phenotypes","volume":"73","author":"Silva","year":"2019","journal-title":"Eur J Clin Nutr"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1139\/h06-031","article-title":"Resistance training reduces whole-body protein turnover and improves net protein retention in untrained young males","volume":"31","author":"Hartman","year":"2006","journal-title":"Appl Nutr Metab"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1186\/s12970-017-0177-8","article-title":"International Society of Sports Nutrition Position Stand: protein and exercise","volume":"14","author":"J\u00e4ger","year":"2017","journal-title":"J Int Soc Sports Nutr"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s12970-017-0189-4","article-title":"International society of sports nutrition position stand: nutrient timing","volume":"14","author":"Kerksick","year":"2017","journal-title":"J Int Soc Sports Nutr"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1088\/0143-0815\/6\/4\/001","article-title":"Nuclear-based techniques for the in vivo study of human body composition. 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