Evidence map›Paper›PMID 33269598›Full record

ArticleJournal of diabetes science and technology2021

Predicting Body Composition From Anthropometrics.

Kong Y Chen

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 49% of its field
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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

1 author at 1 institution in 1 country.

Kong Y ChenDiabetes, Endocrinology, and Obesity Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA.ORCID 0000-0002-0306-1904
National Institute of Diabetes and Digestive and Kidney Diseases · US

Funding

Role of BK-Beta 1 in flow-dependent K+ secretion in the CNTR01DK071014 · NIDDK · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI SANSOM, STEVEN · 2007 to 2015
$2.7M
HTS for Detection of deltaF508 CFTR at the Cell SurfaceR01DK071013 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RIORDAN, JOHN R · 2005 to 2007
$747k
NIDDK NIH HHS R01 DK071013NIDDK NIH HHS R01 DK071014
6 · The paper itself

Abstract

Body weight, height, and other simple, noninvasive anthropometric measures are the cornerstones of epidemiological research. Body composition determinants such as fat and lean tissue masses and their distributions are better associated with metabolic conditions, such as diabetes, than anthropometrics alone. However, body composition is generally more challenging to measure. This analysis article comments on the manuscript by Cichosz et al that appeared in this issue of the

Indexed as

Body CompositionAbsorptiometry, PhotonAnthropometryBody Mass IndexBody WeightHumansRisk Factorsfat distributionfat masslean body massmachine learningmetabolic risks

Identifiers

PMID33269598
PMCPMC8655275
OpenAlexW3109088298

What OpenQuestion 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 OpenQuestion graph.