Evidence map›Paper›PMID 36271961›Full record

ArticleEuropean journal of nutrition2023

Intakes of major food groups in China and UK: results from 100,000 adults in the China Kadoorie biobank and UK biobank.

Keren Papier, Maria G Kakkoura, Yu Guo, Anika Knuppel, Pei Pei, Tammy Y N Tong, Canqing Yu, Aurora Perez-Cornago, Wing Ching Chang, Junshi Chen and 5 more

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

Article in European journal of nutrition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.2field-weighted citation impact, top 21% 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, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

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

15 authors at 5 institutions in 2 countries.

Keren Papier *Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-4102-6835
Maria G Kakkoura *Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK. Maria.Kakkoura@ndph.ox.ac.uk.ORCID http://orcid.org/0000-0003-3688-1367
Yu GuoChinese Academy of Medical Sciences, Beijing, China.
Anika KnuppelMRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK.ORCID http://orcid.org/0000-0003-1049-4836
Pei PeiFuwai Hospital Chinese Academy of Medical Sciences, Beijing, China.
Tammy Y N TongCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-0284-8959
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Aurora Perez-CornagoCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-5652-356X
Wing Ching ChangClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Zhengming ChenClinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Huaidong Du *Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-9814-0049
Timothy J Key *Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0003-2294-307X
University of Oxford · GBPeking University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNChina National Center for Food Safety Risk Assessment · CNMRC Unit for Lifelong Health and Ageing · GB

Funding

British Heart Foundation CH/1996001/9454Cancer Research UK 16491Cancer Research UK 29017Cancer Research UK 29186Cancer Research UK 8221/A29017Cancer Research UK A16491Cancer Research UK A28516Cancer Research UK A29017Cancer Research UK A29186Cancer Research UK C16077/A29186Cancer Research UK C500/A16896Cancer Research UK C570/A16491Cancer Research UK C60192/A28516Medical Research Council G0700474Medical Research Council G9900923Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Medical Research Council MR/K02700X/1Medical Research Council MR/M012190/1Wellcome Trust 088158Wellcome Trust 088158/Z/09/ZWellcome Trust 104085Wellcome Trust 104085/Z/14/ZWellcome Trust 202922Wellcome Trust 202922/Z/16/ZWellcome Trust 205212Wellcome Trust 205212/Z/16/ZWellcome Trust 212946Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

purposeDifferent populations may exhibit differences in dietary intakes, which may result in heterogeneities in diet-disease associations. We compared intakes of major food groups overall, by sex, and by socio-economic status (SES) (defined as both education and income), between participants in the China Kadoorie Biobank (CKB) and the UK Biobank (UKB).

methodsData were from ~ 25,000 CKB participants who completed a validated interviewer-administered computer-based questionnaire (2013-2014) and ~ 74,000 UKB participants who completed ≥ 3 web-based 24-h dietary assessments (2009-2012). Intakes of 12 major food groups and five beverages were harmonized and compared between the cohorts overall, by sex and by SES. Multivariable-adjusted linear regression examined the associations between dietary intakes and body mass index (BMI) in each cohort.

resultsCKB participants reported consuming more rice, eggs, vegetables, soya products, and less wheat, other staple foods (other than rice and wheat), fish, poultry, all dairy products, fruit, and beverages compared to UKB participants. Red meat intake was similar in both cohorts. Having a higher SES was generally associated with a higher consumption of foods and beverages in CKB, whereas in UKB dietary intakes differed more by education and income, with a positive association observed for meat and income in both UKB and CKB but an inverse association observed for education in UKB. Associations of dietary intakes with BMI varied between the two cohorts.

conclusionThe large differences in dietary intakes and their associations with SES and BMI could provide insight into the interpretation of potentially different diet-disease associations between CKB and UKB.

Indexed as

Biological Specimen BanksDietAnimalsChinaFruitMeatUnited KingdomChina Kadoorie BiobankCohort studiesDietary intakeFood groupsUK Biobank

Identifiers

PMID36271961
PMCPMC9941233
OpenAlexW4307091594

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.