Evidence map›Paper›PMID 38637574›Full record

ArticleScientific reports2024

Intake of different types of seafood and meat and risk of type 2 diabetes in women: a prospective study supported by a dietary intervention in mice.

Lene S Myrmel, Jannike Øyen, Anne Lise Brantsæter, Even Fjære, Karen Haugvaldstad, Kåre I Birkeland, Ottar Nygård, Karsten Kristiansen, Grace M Egeland, Lise Madsen

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

10 authors.

Lene S Myrmel *Institute of Marine Research, Nordnes, P.O. Box 1870, 5817, Bergen, Norway.
Jannike Øyen *Institute of Marine Research, Nordnes, P.O. Box 1870, 5817, Bergen, Norway. jannike.oyen@hi.no.
Anne Lise BrantsæterDepartment of Food Safety, Centre for Sustainable Diets, Norwegian Institute of Public Health, Skøyen, P.O. Box 222, 0213, Oslo, Norway.
Even FjæreInstitute of Marine Research, Nordnes, P.O. Box 1870, 5817, Bergen, Norway.
Karen HaugvaldstadInstitute of Marine Research, Nordnes, P.O. Box 1870, 5817, Bergen, Norway.
Kåre I BirkelandDepartment of Transplantation Medicine, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Ottar NygårdCentre for Nutrition, Department of Clinical Science, University of Bergen, Bergen, Norway.
Karsten KristiansenDepartment of Biology, University of Copenhagen, Universitetsparken 13, Copenhagen Ø, Denmark.
Grace M EgelandDepartment of Health Registry Research and Development, Division of Health Data and Digitalisation, Norwegian Institute of Public Health, Sentrum, P.O. Box 973, 5808, Bergen, Norway.
Lise MadsenInstitute of Marine Research, Nordnes, P.O. Box 1870, 5817, Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detailed knowledge regarding the associations between intake of different types of seafood and meat and the risk of type 2 diabetes (T2D), and insight into possible mechanisms are warranted. In this study we aimed to evaluate the associations between intake of different types of seafood and meat and the subsequent risk of T2D using the Norwegian Mother, Father, and Child Cohort Study (MoBa), and furthermore, by using a mouse model to gain further insight into possible molecular mechanisms contributing to the associated metabolic changes. Women in MoBa who were free of pharmacologically treated diabetes at baseline (n = 60,777) were prospectively evaluated for incident T2D, identified on the basis of medication usages > 90 days after delivery, ascertained by the Norwegian Prescription Database. Dietary intake was obtained with a validated 255-item food frequency questionnaire which assessed habitual diet during the first 4-5 months of pregnancy. Metabolic phenotypes and plasma metabolome were investigated in female mice fed isocaloric diets with different types of seafood and meat mimicking the dietary intake in the human cohort. During maximum 10-year and mean (SD) 7.2 (1.6) years follow-up time, 681 (1.1%) women developed pharmacologically treated T2D. All statistical models identified a higher risk of T2D with increased shellfish intake, whereas no associations were observed for total seafood, fatty fish, total meat and red meat in the adjusted models. In mice, the shellfish-based western diet induced reduced glucose tolerance and insulin secretion compared to the diet based on lean fish, and we identified a number of metabolites elevated in plasma from shellfish-fed mice that correlated with glucose intolerance. Mice fed a western diet based on meat also exhibited reduced glucose tolerance in comparison to lean fish fed mice, whereas mice fed fatty fish, total seafood or red meat did not differ from lean fish fed mice. We observed a diet-specific metabolic signature in plasma demonstrating five distinct metabolite profiles in mice fed shellfish, fatty fish, total seafood/lean fish, a mixed diet and meat. In conclusion, these findings demonstrate that different types of seafood have different outcome on T2D risk. In women, intake of shellfish was associated with higher risk of T2D. In female mice, a shellfish enriched diet reduced glucose tolerance and altered the abundance of several distinct plasma metabolites correlating with glucose tolerance.

Indexed as

Diabetes Mellitus, Type 2DietAnimalsCohort StudiesDiet, WesternFemaleGlucoseHumansMeatMicePregnancyProspective StudiesSeafoodGlucoseBMIDietGlucose toleranceMeatMetabolismMetabolomicsMiceProtein intakeProtein sourceSeafoodShellfishType 2 diabetesWomen

Identifiers

PMID38637574
PMCPMC11026463

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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.