Evidence map›Paper›PMID 33125578›Full record

ReviewEuropean journal of nutrition2021

Association between dietary patterns and prediabetes, undetected diabetes or clinically diagnosed diabetes: results from the KORA FF4 study.

Giulia Pestoni, Anna Riedl, Taylor A Breuninger, Nina Wawro, Jean-Philippe Krieger, Christa Meisinger, Wolfgang Rathmann, Barbara Thorand, Carla Harris, Annette Peters and 2 more

Open access · hybridAbstract readReview
In one paragraph

Review in European journal of nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

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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

12 authors at 4 institutions in 2 countries.

Giulia PestoniDivision of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-5933-7439
Anna RiedlIndependent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
Taylor A BreuningerIndependent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.ORCID http://orcid.org/0000-0002-8109-9465
Nina WawroIndependent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.ORCID http://orcid.org/0000-0001-8144-0291
Jean-Philippe KriegerDivision of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-1913-4466
Christa MeisingerIndependent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.ORCID http://orcid.org/0000-0002-9026-6544
Wolfgang RathmannInstitute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.ORCID http://orcid.org/0000-0001-7804-1740
Barbara ThorandGerman Center for Diabetes Research (DZD E.V.), Neuherberg, Germany.
Carla HarrisInstitute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.ORCID http://orcid.org/0000-0002-9003-6976
Annette PetersGerman Center for Diabetes Research (DZD E.V.), Neuherberg, Germany.ORCID http://orcid.org/0000-0001-6645-0985
Sabine RohrmannDivision of Chronic Disease Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-2215-1200
Jakob LinseisenIndependent Research Group Clinical Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, (GmbH), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany. j.linseisen@helmholtz-muenchen.de.ORCID http://orcid.org/0000-0002-9386-382X
University of Augsburg · DEHelmholtz Zentrum München · DEUniversity of Zurich · CHDeutsches Diabetes-Zentrum e.V. · DE

Funding

Bundesanstalt für Landwirtschaft und Ernährung 5.17.02ERNBundesministerium für Bildung und Forschung FK 01EA1807E
6 · The paper itself

Abstract

purposeDiet is one of the most important modifiable risk factors for the development of type 2 diabetes. Here, we aim to identify dietary patterns and to investigate their association with prediabetes, undetected diabetes and prevalent diabetes.

methodsThe present study included 1305 participants of the cross-sectional population-based KORA FF4 study. Oral glucose tolerance test (OGTT) measurements together with a physician-confirmed diagnosis allowed for an accurate categorization of the participants according to their glucose tolerance status into normal glucose tolerance (n = 698), prediabetes (n = 459), undetected diabetes (n = 49), and prevalent diabetes (n = 99). Dietary patterns were identified through principal component analysis followed by hierarchical clustering. The association between dietary patterns and glucose tolerance status was investigated using multinomial logistic regression models.

resultsA Prudent pattern, characterized by high consumption of vegetables, fruits, wholegrains and dairy products, and a Western pattern, characterized by high consumption of red and processed meat, alcoholic beverages, refined grains and sugar-sweetened beverages, were identified. Participants following the Western pattern had significantly higher chances of having prediabetes (odds ratio [OR] 1.92; 95% confidence interval [CI] 1.35, 2.73), undetected diabetes (OR 10.12; 95% CI 4.19, 24.43) or prevalent diabetes (OR 3.51; 95% CI 1.85, 6.67), compared to participants following the Prudent pattern.

conclusionTo our knowledge, the present study is one of the few investigating the association between dietary patterns and prediabetes or undetected diabetes. The use of a reference group exclusively including participants with normal glucose tolerance might explain the strong associations observed in our study. These results suggest a very important role of dietary habits in the prevention of prediabetes and type 2 diabetes.

Indexed as

Diabetes Mellitus, Type 2Prediabetic StateCross-Sectional StudiesDietFeeding BehaviorHumansRisk FactorsDietary patternsGlucose tolerance statusPrediabetesType 2 diabetesUndetected diabetesWestern pattern

Identifiers

PMID33125578
PMCPMC8275503
OpenAlexW3097133818

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.