Evidence map›Paper›PMID 34152010›Full record

ArticleEuropean journal of clinical investigation2021

Associations of toothbrushing behaviour with risks of vascular and nonvascular diseases in Chinese adults.

Zhenhuang Zhuang, Meng Gao, Jun Lv, Canqing Yu, Yu Guo, Zheng Bian, Ling Yang, Huaidong Du, Yiping Chen, Feng Ning and 6 more

Abstract read
In one paragraph

Article in European journal of clinical investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. Pooled it
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  12. [The Relationship Between Oral Microbiota and Chronic Obstructive Pulmonary Disease].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
    Review
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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

16 authors.

Zhenhuang ZhuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Meng GaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Yu GuoChinese Academy of Medical Sciences, Beijing, China.
Zheng BianChinese Academy of Medical Sciences, Beijing, China.
Ling YangMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Huaidong DuMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Yiping ChenMedical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Feng NingNCDs Prevention and Control Department, Qingdao CDC, Qingdao, China.
Huilin LiuNCDs Prevention and Control Department, Hunan CDC, Hunan, China.
Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, China.
Zhengming ChenNuffield Department of Population Health, Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), University of Oxford, Oxford, UK.
Tao HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID https://orcid.org/0000-0002-0328-1368
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
China Kadoorie Biobank (CKB) Collaborative Group

Funding

British Heart Foundation CH/1996001/9454Cancer Research UK 16896Cancer Research UK 29186Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Wellcome Trust 088158Wellcome Trust 104085Wellcome Trust 202922Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

Accumulating evidence has shown that poor oral hygiene is associated with increased risk of cardiometabolic diseases in Western populations. However, its relevance about the relationships in Chinese adults remains unclear. The China Kadoorie Biobank enrolled 512 715 adults aged 30-79 years in China during 2004-2008. Cox regression was used to estimate adjusted hazard ratios (HRs) for each disease associated with measures of oral hygiene. Overall 9.3% of the participants reported rarely or never brushing teeth at baseline. Participants who rarely or never brushed teeth had adjusted HR of 1.12 (95% CI: 1.09, 1.15) for MVE, with similar HRs for stroke (1.08, 1.05-1.12), intracerebral haemorrhage (1.18, 1.11-1.26) and pulmonary heart disease (1.22, 1.13-1.32) compared with those who brushed teeth regularly. Those who did not brush teeth also had increased risk of cancer (1.09, 1.04-1.14), chronic obstructive pulmonary disease (COPD) (1.12, 1.05-1.20), liver cirrhosis (1.25, 1.09-1.44) and all-cause death (1.25, 1.21-1.28) but not type 2 diabetes (0.94, 0.86-1.03) and chronic kidney disease (0.98, 0.81-1.18). Among Chinese adults, we found that poor oral hygiene is associated with higher risks of major vascular disease, cancer, COPD, liver cirrhosis and all-cause deaths, but not type 2 diabetes and chronic kidney disease.

Indexed as

MortalityAdultAgedCardiovascular DiseasesCerebral HemorrhageChinaDiabetes Mellitus, Type 2FemaleHealth BehaviorHumansLiver CirrhosisMaleMiddle AgedNeoplasmsOral HygieneProportional Hazards Modelscardiovascular diseasecohort studydental public healthepidemiologyoral hygiene

Identifiers

PMID34152010
PMCPMC7616900

What OpenQuestion holds

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LicenceCC BY
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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.