Evidence map›Paper›PMID 32414117›Full record

ArticleInternational journal of environmental research and public health2020

Multimorbidity among Two Million Adults in China.

Xiaowen Wang, Shanshan Yao, Mengying Wang, Guiying Cao, Zishuo Chen, Ziting Huang, Yao Wu, Ling Han, Beibei Xu, Yonghua Hu

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 2 pooled it
4.7field-weighted citation impact, top 4% 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

33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 53 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

10 authors at 2 institutions in 2 countries.

Xiaowen WangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Shanshan YaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0002-2125-1242
Mengying WangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.ORCID 0000-0003-0162-5355
Guiying CaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Zishuo ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Ziting HuangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Yao WuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Ling HanDepartment of Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Beibei XuMedical Informatics Center, Peking University Health Science Center, Beijing 100191, China.
Yonghua HuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100191, China.
Peking University · CNYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the multimorbidity prevalence and patterns among middle-aged and older adults from China. Data on thirteen chronic diseases were collected from 2,097,150 participants aged over 45 years between January 1st 2011 and December 31st 2015 from Beijing Medical Claim Data for Employees. Association rule mining and hierarchical cluster analysis were applied to assess multimorbidity patterns. Multimorbidity prevalence was 51.6% and 81.3% in the middle-aged and older groups, respectively. The most prevalent disease pair was that of osteoarthritis and rheumatoid arthritis (OARA) with hypertension (HT) (middle-aged: 22.5%; older: 41.8%). Ischaemic heart disease (IHD), HT, and OARA constituted the most common triad combination (middle-aged: 11.0%; older: 31.2%). Among the middle-aged group, the strongest associations were found in a combination of cerebrovascular disease (CBD), OARA, and HT with IHD in males (lift = 3.49), and CBD, OARA, and COPD with IHD in females (lift = 3.24). Among older patients, glaucoma and cataracts in females (lift = 2.95), and IHD, OARA, and glaucoma combined with cataracts in males (lift = 2.45) were observed. Visual impairment clusters, a mixed cluster of OARA, IHD, COPD, and cardiometabolic clusters were detected. Multimorbidity is prevalent among middle-aged and older Chinese individuals. The observations of multimorbidity patterns have implications for improving preventive care and developing appropriate guidelines for morbidity treatment.

Indexed as

Chronic DiseaseMultimorbidityAgedBeijingChinaComorbidityCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceChinachronic diseasesmultimorbiditypatternprevalence

Identifiers

PMID32414117
PMCPMC7277827
OpenAlexW3024402449

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.