Structural and functional body components in athletic health and performance phenotypes
Abstract
Advances in body composition assessment enable a detailed body composition analyses and the respective organization at different levels. Sports-related professionals are interested in understanding how and which body components are relevant for improving performance, prevent injury risk, and monitor athletic health. The aim of this review is to propose an integrative model that links performance, injury risk, and athletic health with body components, and to report their cross-sectional and longitudinal associations. Cross-sectional studies reveal that endurance athletes with higher fat mass (FM) show a longer race time, whereas a higher fat-free mass benefits power and strength-related tasks. Longitudinal studies indicated that increases in intracellular water, assessed through dilution techniques, were associated with power and strength improvements, independently of weight and lean-soft-tissue changes. There is evidence that athletes involved in weight-sensitive sports restrict energy intake, thus reducing energy availability (EA) and compromising bone health (Female Athlete Triad). To counteract the low EA and related negative energy balance, metabolic adaption (MA) occurs to promote energy conservation. Currently, reference values for body composition assessment using anthropometry and DXA are available for a few sports, according to sex. More research is needed to develop a functional body composition profile according to sports-specific requirements.
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DXA is not considered the state-of-the-art method for evaluating fat and FFM; it should be employed with air plethysmography and dilution techniques according to a four-compartment body composition model.
“although DXA represents one of the most accurate technique for assessing lean soft tissues it is not considered the state-of-the-art method for evaluating fat and FFM, for which it should be employed in conjunction with air plethysmography and dilution techniques according to a four-compartment body composition model [14].”
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“…of the most accurate technique for assessing lean soft tissues it is not considered the state-of-the-art method for evaluating fat and FFM, for which it should be employed in conjunction with air plethysmography and dilution techniques according to a four-compartment body composition model [14].”
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- Authors
- Silva, A. M.
- Affiliations
- University of Lisbon (PT)
- Corresponding author
- Silva, Analiza M.
- ORCID
- Silva, Analiza M.
- Venue
- European Journal of Clinical Nutrition
- Published
- 2018-10-04
- Volume
- 73
- Issue
- 2
- Pages
- 215-224
- ISSN
- 0954-3007 (ISSN-L)
- 1476-5640
- OpenAlex
- W2895022728
- Cited by
- 107
- References
- 91
- Citations by year
- 2026: 14 · 2025: 17 · 2024: 19 · 2023: 12 · 2022: 13 · 2021: 22 · 2020: 6 · 2019: 4
- FWCI
- 1.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- European Journal of Clinical Nutrition (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
- Health Sciences › Medicine › Orthopedics and Sports Medicine › Sports Performance and Training
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Muscle metabolism and nutrition
- Keywords
- body composition, athletic performance, injury risk, fat mass, fat-free mass, intracellular water, energy availability, female athlete triad, bone health, metabolic adaptation, endurance athletes, reference values, dual-energy X-ray absorptiometry, anthropometry
- MeSH terms
- Anthropometry, Body Composition, Humans, Models, Theoretical, Phenotype, Athletic Performance, Athletes
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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