Evidence map›Paper›PMID 30574345›Full record

ArticleObesity science & practice2018

External Validation of Equations that Use Demographic and Anthropometric Measurements to Predict Percent Body Fat.

K R Reynolds, J Stevens, J Cai, C E Lewis, A C Choh, S A Czerwinski

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Obesity science & practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 1 country.

K R ReynoldsDepartments of Epidemiology University of North Carolina Chapel Hill NC US.
J StevensDepartments of Epidemiology University of North Carolina Chapel Hill NC US.ORCID 0000-0001-7306-7298
J CaiDepartments of Biostatistics University of North Carolina Chapel Hill NC US.
C E LewisDivision of Preventive Medicine University of Alabama at Birmingham Birmingham AL US.
A C ChohSchool of Public Health University of Texas Health Science Center at Houston Brownsville TX US.
S A CzerwinskiSchool of Public Health University of Texas Health Science Center at Houston Brownsville TX US.
University of North Carolina at Chapel Hill · USThe University of Texas Health Science Center at Houston · USUniversity of Alabama at Birmingham · US

Funding

Percent body fat equations for the United States PopulationR01DK097046 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI STEVENS, JUNE · 2014 to 2015
$648k
NHLBI NIH HHS HHSN268201300029CNIDDK NIH HHS R01 DK097046
6 · The paper itself

Abstract

objectiveNumerous equation to predict percent body fat using demographics and anthropometrics have been published but external validation of these equations is limited. The objective of this study was to validate published equations that use anthropometrics for prediction of percent body fat using external data.

methodsData were from the Visceral Fat, Metabolic Rate, and Coronary Heart Disease Risk I (VIM I) Study and the Fels Longitudinal Study (Fels). VIM I was conducted in a subset of subjects from the CARDIA study and included black and white adults 28-40 years (

resultsIn general, the Stevens equations performed better than equations from other studies. For example, equation "I" in women in VIM I, Fels adults, and Fels youth, R

conclusionsOur results indicate that several of the Stevens equations have external validity superior to that of nine other published equations among varying age groups, genders and races.

Indexed as

Adipositybody compositionDXA

Identifiers

PMID30574345
PMCPMC6298207
OpenAlexW2891705342

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.