Evidence map›Paper›PMID 34330847›Full record

ArticleRMD open2021

Food sources of dietary fibre and risk of total knee replacement related to severe osteoarthritis, the Singapore Chinese Health Study.

Ying Ying Leung, Aizhen Jin, Kelvin Bryan Tan, Li-Wei Ang, Jian-Min Yuan, Woon-Puay Koh

Abstract read
In one paragraph

Article in RMD open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ying Ying LeungRheumatology & Immunology, Singapore General Hospital, Singapore katyccc@hotmail.com.ORCID 0000-0001-8492-6342
Aizhen JinHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Kelvin Bryan TanGovernment of Singapore Ministry of Health, Singapore.
Li-Wei AngGovernment of Singapore Ministry of Health, Singapore.
Jian-Min YuanDivision of Cancer Control and Population Sciences, UPMC Hillman Cancer Centre, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Woon-Puay KohHealthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.

Funding

Prospective studies of cancer etiology and prevention in Shanghai and SingaporeR01CA144034 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2010 to 2014
$7.0M
THE SINGAPORE COHORT STUDY OF DIET AND CANCERR01CA080205 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YUAN, JIAN-MIN · 1999 to 2009
$5.3M
Cancer epidemiology cohorts in Shanghai and Singapore UM1CA182876 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2014 to 2018
$4.3M
NCI NIH HHS R01 CA080205NCI NIH HHS R01 CA144034NCI NIH HHS UM1 CA182876
6 · The paper itself

Abstract

objectivesWe aimed to evaluate the association between fibre intake and its food sources, and the risk of total knee replacement (TKR) due to severe knee osteoarthritis (KOA).

methodsWe used data from the Singapore Chinese Health Study, a prospective cohort study that recruited 63 257 participants aged 45-74 years from 1993 to 1998. At baseline, we assessed diet using a validated 165-item semiquantitative food frequency questionnaire, together with body mass index (BMI) and lifestyle factors. Incident TKR cases were identified via record linkage with nationwide hospital discharge database through 2017.

resultsThere were 2816 cases of incident TKR due to severe KOA. The total fibre intake at baseline was not associated with the risk of TKR after adjustment for confounders. Among the food sources of fibre, higher intake of legumes was associated with a lower risk of TKR in a dose-dependent manner; compared with those having the lowest quartile intake, HR (95% CI) was 0.86 (0.76, 0.96) for those having the highest quartile intake (p for trend=0.004). This association was consistent after including BMI in the model and homogeneous across BMI categories. The consumption of other fibre sources, namely grain products, nuts and seeds, soy food, fruits and vegetables, was not associated with the risk of TKR.

conclusionIntake of legumes, but not total fibre, was associated with a reduced risk of TKR. Further research is needed to replicate our findings and to evaluate possible biological mechanisms that could explain the effect of dietary legumes on pathogenesis or progression of KOA.

Indexed as

Arthroplasty, Replacement, KneeOsteoarthritis, KneeChinaDietary FiberHumansProspective StudiesSingaporeDietary Fiberepidemiologykneeosteoarthritis

Identifiers

PMID34330847
PMCPMC8327838

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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.