Evidence map›Paper›PMID 35267955›Full record

ArticleNutrients2022

The Prospective Associations of Lipid Metabolism-Related Dietary Patterns with the Risk of Diabetes in Chinese Adults.

Qi Liu, Qiaorui Wen, Jun Lv, Zumin Shi, Yu Guo, Pei Pei, Huaidong Du, Ling Yang, Yiping Chen, Xiaofang Zhang and 7 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

6 citing papers in PubMed, 6 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

17 authors at 6 institutions in 3 countries.

Qi LiuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Qiaorui WenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
Zumin ShiHuman Nutrition Department, College of Health Sciences, QU Health, Qatar University, Doha 2713, Qatar.ORCID 0000-0002-3099-3299
Yu GuoNational Center for Cardiovascular Diseases, Fuwai Hospital Chinese Academy of Medical Sciences, Beijing 100730, China.
Pei PeiChinese Academy of Medical Sciences, Beijing 100730, China.
Huaidong DuMedical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK.
Ling YangMedical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK.
Yiping ChenMedical Research Council Population Health Research Unit, University of Oxford, Oxford OX3 7LF, UK.
Xiaofang ZhangMaiji Center for Disease Control and Prevention, Tianshui 741020, China.
Dan SchmidtClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Sam SansomeClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Junshi ChenNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing 100022, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.ORCID 0000-0002-0019-0014
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
On Behalf Of The China Kadoorie Biobank Ckb Collaborative Group
University of Oxford · GBPeking University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNChina National Center for Food Safety Risk Assessment · CNGansu Great Wall Electrical and Electronics Engineering Research Institute · CNQatar University · QA

Funding

Cancer Research UK 29186Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2National Key Research and Development Program of China 2016YFC0900500, 2016YFC0900501, 2016YFC090050National Natural Science Foundation of China 81973125Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundThis study aimed to identify lipid metabolism-related dietary patterns with reduced rank regression (RRR) among Chinese adults and examine their associations with incident diabetes.

methodsWe derived lipid metabolism-related dietary patterns using an RRR with 21 food groups as predictors as well as total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, body mass index (BMI), and waist circumference from the responses of 17,318 participants from the second resurvey of the China Kadoorie Biobank (CKB). The dietary scores were calculated for the entire cohort. We followed up 479,207 participants for diabetes incidence from the baseline and used multivariable Cox regression models to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs).

resultsTwo lipid metabolism-related dietary patterns were extracted. The dietary pattern-characterized by high intakes of fish, poultry, and other staples as well as fresh fruit and vegetables-was correlated with a higher BMI, waist circumference, and LDL cholesterol. Participants in the highest quintile (Q5) had a 44% increased risk of diabetes incidence when compared with those in the lowest quintile (Q1) (HR = 1.44; 95% CI: 1.31-1.59).

conclusionsA dietary pattern characterized by high intakes of both animal and plant foods was related to obesity and dyslipidemia and could increase the risk of diabetes incidence.

Indexed as

Diabetes MellitusLipid MetabolismAsian PeopleDietHumansVegetablesdiabetesdietary patternslipid metabolismreduced rank regression

Identifiers

PMID35267955
PMCPMC8912567
OpenAlexW4214575842

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.