Evidence map›Paper›PMID 34323047›Full record

ArticleSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition2021

[Dietary Patterns and Their Association with Diabetes Mellitus in Middle-Aged and Older Rural Population in Xinxiang County, Henan Province].

Hui-Jun Li, Wen-Long Li, Hui Wu, Hai-Bin Li, Yong-Bin Wang, Zhen An, Jing Jiang, Wei-Dong Wu

Open access · greenAbstract read
In one paragraph

Article in Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 30% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
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

8 authors at 1 institution in 1 country.

Hui-Jun LiSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Wen-Long LiSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Hui WuSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Hai-Bin LiSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Yong-Bin WangSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Zhen AnSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Jing JiangSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Wei-Dong WuSchool of Public Health, Xinxiang Medical University/Henan International Collaborative Laboratory for Health Effects and Intervention of Air Pollution, Xinxiang 453003, China.
Xinxiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze the prevalence of diabetes mellitus among middle-aged and older rural adults of Xinxiang county, Henan Province and its correlation with dietary patterns.

methodsThe study was done based on the data collected from a cross-sectional survey of Xinxiang County, which was part of the Prospective Cohort Study on the Common Chronic Non-Communicable Diseases in Rural areas of Henan Province. Randomized cluster sampling was used to select adult respondents (≥18 years old) from among the residents of 17 villages in Xinxiang county. The respondents completed questionnaires, and underwent physical examinations and laboratory tests between April, 2017 and June, 2017. A total of 7604 individuals aged between 45 and 79 were included in our study. Dietary patterns were established through factor analysis and the dietary pattern factor scores were divided into quartiles (Q1-Q4). The relationship between dietary patterns and diabetes mellitus was analyzed with multivariate logistic regression model.

resultsOut of the total of 7604 middle-aged and older rural adults in Xinxiang County, Henan Province, 1604 had diabetes mellitus, suggesting a 21.1% prevalence of diabetes mellitus. Factor analysis was used to establish four dietary patterns, namely animal-based diet, vegetable-egg diet, mixed diet and traditional diet. Subjects of these four dietary patterns displayed different demographic characteristics. There were no statistical difference in anthropometricor clinical indicators between the quartile with the lowest dietary pattern factor score (Q1) and the quartile with the highest dietary pattern factor score (Q4) for subjects with animal-based diet (

conclusionThe prevalence of diabetes in middle-aged and older rural residents is relatively high in Xinxiang County, Henan Province, and there may be a protective relationship between traditional diet and diabetes mellitus.

Indexed as

Diabetes MellitusRural PopulationAdolescentAdultAgedAnimalsChinaCross-Sectional StudiesDietHumansMiddle AgedProspective StudiesRisk FactorsDiabetes mellitusDietary patternMiddle-aged and older adultsRural residents

Identifiers

PMID34323047
PMCPMC10409393
OpenAlexW3183202428

What OpenQuestion holds

Textmetadata
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.