ArticleInternational journal of body composition research2013
Estimation of whole body fat from appendicular soft tissue from peripheral quantitative computed tomography in adolescent girls.
Article in International journal of body composition research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- "One-stop-shop" medical imaging for osteoporosis and obese patients: a narrative review.Journal of endocrinological investigation · 2026Review
- Assessment of whole-body and regional body fat using abdominal quantitative computed tomography in Chinese women and men.Lipids in health and disease · 2024Article
- Validation of Peripheral Quantitative Computed Tomography-Derived Thigh Adipose Tissue Subcompartments in Young Girls Using a 3 T MRI Scanner.Journal of clinical densitometry : the official journal of the International Society for Clinical DensitometryArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectiveAssess the utility of peripheral quantitative computed tomography (pQCT) for estimating whole body fat in adolescent girls. RESEARCH METHODS AND PROCEDURES: Our sample included 458 girls (aged 10.7 ± 1.1y, mean BMI = 18.5 ± 3.3 kg/m
resultsThigh and calf SFA %Fat were positively correlated with DXA %Fat (r = 0.84 to 0.85; DISCUSSION: Peripheral QCT derived indices of adiposity can be used to accurately estimate whole body percent fat in adolescent girls.
Indexed as
Identifiers
25147482PMC4137877What OpenQuestion holds
Registered trials
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 OpenQuestion graph.