Evidence map›Paper›PMID 37892537›Full record

SynthesisNutrients2023

The Association between the EAT-Lancet Diet and Diabetes: A Systematic Review.

Xiaoxiao Lin, Shuai Wang, Jinyu Huang

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 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

3 authors at 2 institutions in 1 country.

Xiaoxiao LinAffiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310030, China.
Shuai WangAffiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310030, China.
Jinyu HuangAffiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310030, China.
Hangzhou First People's Hospital · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several studies have explored the association between diabetes and the EAT-Lancet diet. Thus, the objective of our study was to conduct a systematic review to analyze and summarize all clinical studies concerning the association between diabetes and the EAT-Lancet diet. We undertook a comprehensive search of the Embase, Cochrane, and PubMed databases up to 15 August 2023. All clinical studies concerning the association between diabetes and the EAT-Lancet diet were summarized and analyzed. In total, our systematic review included five studies of four prospective studies and one cross-sectional study, encompassing 259,315 participants. All the included studies were evaluated as high quality. The outcomes from all studies indicated that adherence to the EAT-Lancet diet was correlated with a reduced risk of diabetes. In conclusion, the EAT-Lancet diet may be an effective dietary intervention for diabetes. Nevertheless, the number of studies examining the association between diabetes and the EAT-Lancet diet is limited. Further high-quality studies are required to expand our understanding of the benefits of the EAT-Lancet diet for patients with diabetes.

Indexed as

Diabetes Mellitus, Type 2DietCross-Sectional StudiesHumansProspective StudiesassociationbenefitsdiabetesEAT–Lancet dietsystematic review

Identifiers

PMID37892537
PMCPMC10610026
OpenAlexW4387843766

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.