Evidence map›Paper›PMID 39798028›Full record

ReviewCurrent obesity reports2025

Updates on Methods for Body Composition Analysis: Implications for Clinical Practice.

Diana M Thomas, Ira Crofford, John Scudder, Brittany Oletti, Ashok Deb, Steven B Heymsfield

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current obesity reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Review
  2. Article
  3. Future of CT body composition research: Methodological discrepancies and advances.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2026
    Review
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Association between body fat percentage and metabolic and hematologic biomarkers in Korean adults.The Korean journal of physiology & pharmacology : official journal of the Korean Physiological Society and the Korean Society of Pharmacology · 2026
    Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Diana M ThomasDepartment of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA. diana.thomas@westpoint.edu.
Ira CroffordDepartment of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA.
John ScudderDepartment of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA.
Brittany OlettiDepartment of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA.
Ashok DebDepartment of Mathematical Sciences, United States Military Academy, West Point, NY, 10996, USA.
Steven B HeymsfieldMetabolism and Body Composition, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA.

Funding

NIH HHS IAA AOD22022001
6 · The paper itself

Abstract

backgroundRecent technological advances have introduced novel methods for measuring body composition, each with unique benefits and limitations. The choice of method often depends on the trade-offs between accuracy, cost, participant burden, and the ability to measure specific body composition compartments.

objectiveTo review the considerations of cost, accuracy, portability, and participant burden in reference and emerging body composition assessment methods, and to evaluate their clinical applicability.

methodsA narrative review was conducted comparing traditional reference methods like dual-energy X-ray absorptiometry (DXA), magnetic resonance imaging (MRI), and computed tomography (CT) with emerging technologies such as smartphone camera applications, three-dimensional optical imaging scanners, smartwatch bioelectric impedance analysis (BIA), and ultrasound.

resultsReference methods like CT and MRI offer high accuracy and the ability to distinguish between specific body composition compartments (e.g., visceral, subcutaneous, skeletal muscle mass, and adipose tissue within lean mass) but are expensive and non-portable. Conversely, emerging methods, such as smartwatch BIA and smartphone-based technologies, provide greater accessibility and lower participant burden but with reduced accuracy. Methods like three-dimensional optical imaging scanners balance portability and accuracy, presenting promising potential for population-level applications.

conclusionsThe selection of a body composition assessment method should be guided by the clinical context and specific application, considering trade-offs in cost, accuracy, and portability. Emerging methods provide valuable options for population-level assessments, while reference methods remain essential for detailed compartmental analysis.

Indexed as

Absorptiometry, PhotonBody CompositionElectric ImpedanceMagnetic Resonance ImagingHumansSmartphoneTomography, X-Ray ComputedUltrasonography2D Smartphone Camera Technology3D Body Optical ImagingBody CompositionBody Impedance AnalysisComputed TomographyDual Energy X-Ray AbsorptiometryFat Free MassFat MassMagnetic Resonance ImagingSmartwatch BIA TechnologyUltrasoundVisceral Adipose Tissue

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.