Evidence map›Paper›PMID 36062135›Full record

ArticleFrontiers in public health2022

The impact of potentially modifiable risk factors for stroke in a middle-income area of China: A case-control study.

Yuhang Wu, Xiaoyun Chen, Songbo Hu, Huilie Zheng, Yiying Chen, Jie Liu, Yan Xu, Xiaona Chen, Liping Zhu, Wei Yan

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

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  7. Which risk factors significantly influence the outcome of traumatic brain injured patients with alcohol use disorder?European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
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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 1 country.

Yuhang WuJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Xiaoyun ChenJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Songbo HuJiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang, Jiangxi, China.
Huilie ZhengJiangxi Province Key Laboratory of Preventive Medicine, School of Public Health, Nanchang University, Nanchang, Jiangxi, China.
Yiying ChenJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Jie LiuJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Yan XuJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Xiaona ChenJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Liping ZhuJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Wei YanJiangxi Center for Disease Control and Prevention Institute of Chronic Non-communicable Diseases, Nanchang, China.
Nanchang Center for Disease Control and Prevention · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: To reveal the impact of eleven risk factors on stroke and provide estimates of the prevention potential. Methods: We completed a multicenter case-control study in Jiangxi, China, a middle-income area. Neuroimaging examination was performed in all cases. Controls were stroke-free adults recruited from the community in the case concentration area. Conditional logistic regression and unconditional logistic regression were used for subgroup analysis of stroke type, and other groups (sex, age and urban-rural area), respectively. Odds ratios (ORs) and their population attributable risks (PARs) were calculated, with 95% confidence intervals. Results: A total of 43,615 participants (11,735 cases and 31,880 controls) were recruited from February to September 2018, of whom we enrolled 11,729 case-control pairs. Physical inactivity [PAR 69.5% (66.9-71.9%)] and hypertension [53.4% (49.8-56.8%)] were two major risk factors for stroke, followed by high salt intake [23.9% (20.5-27.3%)], dyslipidemia [20.5% (17.1-24.0%)], meat-based diet [17.5% (14.9-20.4%)], diabetes [7.7% (5.9-9.7%)], cardiac causes [5.3% (4.0-6.7%)], alcohol intake [4.7% (0.2-10.0%)], and high homocysteine [4.3% (1.4-7.4%)]. Nine of these factors were associated with ischemic stroke, and five were associated with intracerebral hemorrhage. Collectively, eleven risk factors accounted for 59.9% of the PAR for all stroke (ischemic stroke: 61.0%; intracerebral hemorrhage: 46.5%), and were consistent across sex (men: 65.5%; women: 62.3%), age (≤55: 65.2%; >55: 63.5%), and urban-rural areas (city: 62.2%; county: 65.7%). Conclusion: The 11 risk factors associated with stroke identified will provide an important reference for evidence-based planning for stroke prevention in middle-income areas. There is an urgent need to improve awareness, management and control of behavioral and metabolic risk factors, particularly to promote physical activity and reduce blood pressure.

Indexed as

Ischemic StrokeStrokeAdultCase-Control StudiesCerebral HemorrhageChinaFemaleHumansMaleRisk Factorscase-control studyChinesepopulation attributable risksrisk factorsstroke

Identifiers

PMID36062135
PMCPMC9437343
OpenAlexW4292372624

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.