Evidence map›Paper›PMID 37855120›Full record

ArticlePublic health nutrition2023

Flavour, emulsifiers and colour are the most frequent markers to detect food ultra-processing in a UK food market analysis.

Nathalie Judith Neumann, Gerrit Eichner, Mathias Fasshauer

Abstract read
In one paragraph

Article in Public health nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

3 authors.

Nathalie Judith NeumannInstitute of Nutritional Science, Justus-Liebig University of Giessen, Goethestr. 55, Giessen, Hessen35390, Germany.ORCID 0000-0003-3247-1555
Gerrit EichnerMathematical Institute, Justus-Liebig University of Giessen, Giessen, Germany.
Mathias FasshauerInstitute of Nutritional Science, Justus-Liebig University of Giessen, Goethestr. 55, Giessen, Hessen35390, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo elucidate which markers of ultra-processing (MUP) and their combinations are best suited to detect ultra-processed food (UPF).

designThe study was based on the 206 food and 32 beverage items of the Oxford WebQ which encompass all major foods consumed in the UK. For each Oxford WebQ question, ingredient lists of up to ten matching different commercial products (

settingCross-sectional analysis.

participantsNone.

resultsA total of 990 products contained at least one MUP and were, therefore, regarded as UPF. The most frequent MUP were flavour (578 items, 58·4 % of all UPF), emulsifiers (353 items, 35·7 % of all UPF) and colour (262 items, 26·5 % of all UPF). Combined, these three MUP detected 79·2 % of all UPF products. Detection rate increased to 88·4 % of all UPF if ingredient lists were analysed concerning three additional MUP, that is, fibre, dextrose and firming agent.

conclusionsAlmost 90 % of all UPF items can be detected by six MUP.

Indexed as

DietFood HandlingColorCross-Sectional StudiesFast FoodsHumansUnited KingdomFood additivesMarkers of ultra-processingNOVA classificationUltra-processed food

Identifiers

PMID37855120
PMCPMC10755427

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Registered trials

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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.