Evidence map›Paper›PMID 41173369›Full record

ArticleThe Journal of nutrition2026

Reproducibility and Sources of Variation of Urinary Biomarkers of Food Intake of Fruits, Vegetables, and Chocolate in European Children and Adolescents.

Jantje Goerdten, Jodi Rattner, Mira Merdas, David Achaintre, Li Yuan, Paola Russo, Toomas Veidebaum, Dénes Molnár, Lauren Lissner, Stefaan De Henauw and 7 more

Abstract read
In one paragraph

Article in The Journal of nutrition, 2026. 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
–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

1 citing paper in PubMed.

  1. Review
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

17 authors.

Jantje GoerdtenLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany. Electronic address: goerdten@leibniz-bips.de.
Jodi RattnerNutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.
Mira MerdasNutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.
David AchaintreNutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France; Department of Environmental Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States; The Institute for Exposomics Research, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Li YuanLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Paola RussoInstitute of Food Sciences, National Research Council, Avellino, Italy.
Toomas VeidebaumNational Institute for Health Development, Estonian Centre of Behavioral and Health Sciences, Tallinn, Estonia.
Dénes MolnárDepartment of Pediatrics, Medical School, University of Pécs, Pécs, Hungary.
Lauren LissnerSchool of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Stefaan De HenauwDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Luis A MorenoGENUD (Growth, Exercise, Nutrition and Development) Research Group, Faculty of Health Sciences, University of Zaragoza, Instituto Agroalimentario de Aragón (IA2) and Instituto de Investigación Sanitaria Aragón (IIS Aragón), Zaragoza, Spain; Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.
Krasimira AleksandrovaLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Faculty of Human and Health Sciences, University of Bremen, Bremen, Germany.
Ronja ForaitaLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
Ute NöthlingsUnit of Nutritional Epidemiology, Department of Nutrition and Food Sciences, Rheinische Friedrich-Wilhelms-University Bonn, Bonn, Germany.
Pekka Keski-RahkonenNutrition and Metabolism Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France.
Anna FloegelLeibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany; Section of Nutrition and Dietetics, Faculty of Agriculture and Food Sciences, Hochschule Neubrandenburg - University of Applied Sciences, Neubrandenburg, Germany.
IDEFICS/I.Family Consortia

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundBiomarkers of food intake may improve dietary assessment. Thereby, a key concern is their reproducibility over time. In epidemiological studies, it is important to accurately estimate habitual food intake and consequent disease risk associations.

objectivesWe aimed to assess the reproducibility of 12 urinary metabolites linked to food intake and to investigate potential sources of their variation.

methodsThe analyses are based on previously identified urinary metabolites associated with dietary intake of fruits, vegetables, and chocolate in the large-scale European Identification and Prevention of Dietary- and Lifestyle-Induced Health Effects in Children and Infants/I.Family study. Metabolites were measured in 1788 urine samples from 599 children at study baseline (2007/2008, n = 597), at the first follow-up (2009/2010, n = 596), and at the third follow-up (2013/2014, n = 595) using high-resolution liquid chromatography-MS. Unadjusted and adjusted intraclass correlation coefficients (ICCs) were calculated for 2- and 4-y intervals. To identify sources of biomarker variability, various factors, including dietary intake, were analyzed. The amount of variance explained by each factor was quantified using the partial coefficient of determination (R

resultsThe median ICCs were 0.27 (range: 0.11-0.54) and 0.28 (range: 0.15-0.51) over 2- and 4-y intervals, respectively. Individual factors explained a median of 17% (range: 9.8-42.4) of the variance for the 2-y interval and 14.6% (range: 8.3-43.8) for the 4-y interval. Country of residence explained the largest proportion of variance (median: 5% for the 2-y interval, 4.5% for the 4-y interval). Dietary intake explained only a variation of 0.7% (0.0-1.5) and 0.6% (0.0-1.1) for the 2- and 4-y interval, respectively.

conclusionsThe reproducibility of urinary metabolites was poor to moderate over the 2- to 4-y periods, and only part of the variability could be explained by the studied factors. Future studies should explore shorter time intervals and other sources of variation, e.g., the influence of the gut microbiome and genetic factors.

Indexed as

BiomarkersChocolateDietFruitVegetablesAdolescentChildChild, PreschoolEatingEuropeFeeding BehaviorFemaleHumansMaleReproducibility of ResultsBiomarkersbiomarkers of food intakemetabolitesmetabolomicsreproducibilityurinevariability

Identifiers

PMID41173369
PMCPMC12881672

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.