Evidence map›Paper›PMID 39730368›Full record

ArticleNPJ science of food2024

Utilization of plant-based foods for effective prevention of chronic diseases: a longitudinal cohort study.

Jie Liang, Yanchao Wen, Jinzhu Yin, Guiming Zhu, Tong Wang

Abstract read
In one paragraph

Article in NPJ science of food, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
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

5 authors.

Jie Liang *Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Yanchao Wen *Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Jinzhu YinDepartment of Neurosurgery/Shanxi Health Commission Key Laboratory of Nervous System Disease Prevention and Treatment, Sinopharm Tongmei General Hospital, Datong, Shanxi, China.
Guiming ZhuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China.
Tong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China. tongwang@sxmu.edu.cn.

Funding

National Natural Science Foundation of China 82304254National Natural Science Foundation of China 82373692Open Project of Shanxi Health Commission Key Laboratory of Nervous System Disease Prevention and Treatment TMSYSKF2023005the Youth Project of Shanxi Basic Research 202303021212145
6 · The paper itself

Abstract

The present study examined optimal dietary patterns of eight plant-based foods for preventing chronic diseases, including hypertension, stroke, myocardial infarction, and diabetes, using data from the China Health and Nutrition Survey (CHNS). We applied generalized estimating equations to assess time-based changes and gender differences, using residual balancing weights to control time-varying confounders, and employed a restricted cubic spline model to explore dose-response relationships by gender. The findings suggested that a high intake of vegetables and whole grains, along with moderate amounts of fruits, fungi and algae, could help reduce the risk of developing these four chronic diseases simultaneously. Additionally, men could benefit from moderate refined grain consumption, while women should consider increasing their intake of nuts and seeds. Our results indicated that adopting a plant-based diet could provide non-linear protective effects against chronic diseases, with the magnitude of this protection varying by gender.

Identifiers

PMID39730368
PMCPMC11680596

What OpenQuestion holds

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Registered trials

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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.