Evidence mapPaperPMID 41277987Full record

ArticleMethodsX2025

Cleaning and using FooDB: a method for extracting compound information and applying FooDB in dietary cohort studies.

Meike E Vos, Marie Y Meima, Geert F Houben

Abstract read
In one paragraph

Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Meike E VosThe Netherlands Organization for Applied Scientific Research, Princetonlaan 6, 3584 CB Utrecht, The Netherlands.
Marie Y MeimaThe Netherlands Organization for Applied Scientific Research, Princetonlaan 6, 3584 CB Utrecht, The Netherlands.
Geert F HoubenThe Netherlands Organization for Applied Scientific Research, Princetonlaan 6, 3584 CB Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food plays a large role in health and disease. Foods consist of an incredible number of different compounds, many of which are responsible for (yet unknown) biological effects. To research health effects of food compounds, food composition databases are essential for deriving compound concentrations in foods. Many such databases are limited to around 100 compounds, but FooDB, the largest food composition database, aggregates data from different sources, expanding the number of compounds to more than 10,000. These data require cleaning before it can be used in compound intake analyses. This paper describes a method to clean and standardize FooDB for compound-centric dietary intake analyses.

Indexed as

Data cleaningDietary cohort dataDietary intake dataDTUDUKEFood compositionFood compounds databaseFood intakeMacronutrientsMicronutrientsNEVOPhenol-explorerPolyphenolsUSDAWord embeddings

Identifiers

PMID41277987
PMCPMC12637271

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.