Evidence map›Paper›PMID 33809363›Full record

ArticleSensors (Basel, Switzerland)2021

Model Development for Fat Mass Assessment Using Near-Infrared Reflectance in South African Infants and Young Children Aged 3-24 Months.

Alexander Miller, Jacqueline Huvanandana, Peter Jones, Heather Jeffery, Angela Carberry, Christine Slater, Alistair McEwan

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

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 97% 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, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Validity of non-traditional measures of obesity compared to total body fat across the life course: A systematic review and meta-analysis.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Pooled it
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

7 authors at 2 institutions in 2 countries.

Alexander MillerSchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.
Jacqueline HuvanandanaSchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.
Peter JonesSchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.ORCID 0000-0002-0229-3527
Heather JefferySchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.
Angela CarberrySchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.
Christine SlaterIndependent Consultant, Maryport CA15, UK.
Alistair McEwanSchool of Electrical and Information Engineering, University of Sydney, Darlington, NSW 2008, Australia.ORCID 0000-0001-7597-6372
The University of Sydney · AUMaryport Victoria Cottage Hospital · GB

Funding

Bill and Melinda Gates Foundation OPP1111820
6 · The paper itself

Abstract

Undernutrition in infants and young children is a major problem leading to millions of deaths every year. The objective of this study was to provide a new model for body composition assessment using near-infrared reflectance (NIR) to help correctly identify low body fat in infants and young children. Eligibility included infants and young children from 3-24 months of age. Fat mass values were collected from dual-energy x-ray absorptiometry (DXA), deuterium dilution (DD) and skin fold thickness (SFT) measurements, which were then compared to NIR predicted values. Anthropometric measures were also obtained. We developed a model using NIR to predict fat mass and validated it against a multi compartment model. One hundred and sixty-four infants and young children were included. The evaluation of the NIR model against the multi compartment reference method achieved an r value of 0.885, 0.904, and 0.818 for age groups 3-24 months (all subjects), 0-6 months, and 7-24 months, respectively. Compared with conventional methods such as SFT, body mass index and anthropometry, performance was best with NIR. NIR offers an affordable and portable way to measure fat mass in South African infants for growth monitoring in low-middle income settings.

Indexed as

Adipose TissueBody CompositionAbsorptiometry, PhotonAdolescentAdultAnthropometryBody Mass IndexChildChild, PreschoolHumansInfantYoung Adultdeuterium dilution (DD)dual energy X-ray absorptiometry (DXA)fat mass (FM)near-infrared reflectance (NIR)

Identifiers

PMID33809363
PMCPMC8001761
OpenAlexW3137889434

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.