Evidence map›Paper›PMID 32311944›Full record

ArticleMedicine2020

The population attributable risk and clustering of stroke risk factors in different economical regions of China.

Shuju Dong, Jinghuan Fang, Yanbo Li, Mengmeng Ma, Ye Hong, Li He

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 8 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

6 authors at 1 institution in 3 countries.

Shuju DongDepartment of Neurology, West China Hospital, Sichuan University, Chengdu, China.
Jinghuan Fang
Yanbo Li
Mengmeng Ma
Ye Hong
Li He
National Natural Science Foundation of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The greatest regional variation in stroke prevalence exists in China. However, whether there are differences in population attributable risk (PAR) and clustering of stroke risk factors among regions resulting in stroke geographic variation is unclear.We conducted face-to-face surveys of residents of 14 provinces from September 2016 to May 2017 who participated in the Chinese Stroke Screening and Prevention Project. We compared the specific PAR values of eight risk factors and the different cluster rates and patterns in China.A total of 84,751partipants were included. Eight factors accounted for 70% to 80% of the PAR of overall stroke in China. Not only did the PAR of the total risk factors differ among the 3 regions, but the PAR of the same risk factor also varied among different regions. The top 3 factors with the greatest PAR variations among the 3 regions were dyslipidemia, physical inactivity and family history of stroke. The clustering rates and patterns varied by regions. The overall proportion of participants with 0, 1, 2, 3, and ≥4 risk factors were 34.4%, 28.0%, 17.4%, 9.2%, and 10.3% in eastern China; 31.0%, 27.9%, 19.8%, 10.8%, and 9.9% in Central China and 28.2%, 29.5%, 19.9%, 10.8%, and 11.0% in western China, respectively. On basis of hypertension, the most common risk cluster patterns were overweight or smoking, dyslipidemia and physical inactivity, with other risk factors in the eastern, central and western regions, respectively.The rates and patterns of clustering and the potential importance of stroke risk factors in different regions may together contribute to the geographical variation in stroke prevalence in China.

Indexed as

ChinaCluster AnalysisCross-Sectional StudiesFemaleFollow-Up StudiesGeography, MedicalHumansMaleMiddle AgedRisk FactorsStrokeSurveys and Questionnaires

Identifiers

PMID32311944
PMCPMC7220510
OpenAlexW3016467842

What Socratic holds

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LicenceCC BY-NC
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 Socratic graph.