Evidence map›Paper›PMID 36424109›Full record

ArticleBMJ open2022

Distribution of risk factors differs from coronary heart disease and stroke in China: a national population survey.

Yapeng Li, Ling Yin, Ying Shen, Anran Wang, Lue Zhou, Yuan Gao, Yusheng Li, Jie Lu, Songhe Shi, Chuansheng Tian and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Diagnostic Value of miR-1225-5p in Acute Coronary Syndrome and its Mechanism in ox-LDL Induced Human Coronary Artery Endothelial Cells Injury.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    Article
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

13 authors.

Yapeng LiDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.ORCID 0000-0003-3412-0652
Ling YinDepartment of Neurology, the Chinese PLA General Hospital, Beijing, China.
Ying ShenDepartment of Traditional Chinese Medicine, Xuanwu Hospital of Capital Medical University, Beijing, China.
Anran WangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Lue ZhouDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yuan GaoDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yusheng LiDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Jie LuDepartment of Epidemiology and Health Statistics, Zhengzhou University, Zhengzhou, China.
Songhe ShiDepartment of Epidemiology and Health Statistics, Zhengzhou University, Zhengzhou, China.
Chuansheng TianChinese Preventive Medicine Association, Beijing, China.
Yuming XuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Longde WangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China longde_wang@yeah.net.
China National Stroke Screening Survey investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to explore the distribution differences of common risk factors between coronary heart disease (CHD) and stroke in China.

settingThe China National Stroke Screening Survey is a cluster sampling survey based on a nationwide general community population, adopting multistage stratified sampling method and covering all 31 provinces in China mainland.

participantsA total number of 725 707 people aged 40 years and above were included in the study. PRIMARY AND SECONDARY OUTCOME MEASURES: The basic demographic information, lifestyle behaviour, physical examination, traditional risk factors, family history of cardiovascular disease (CVD) and CVD events were collected. Risk factors of CHD and stroke were explored and analysed in the whole investigated population to identify the common risk factors. Multivariate logistic regression analysis was used to analyse the distribution difference of risk factors between CHD and stroke.

resultsThere were 13 variables associated with CHD and stroke, in which 11 variables revealed differences in the distribution between CHD and stroke. Family history of stroke (OR: 2.30; 95% CI 2.15 to 2.45), men (OR: 1.92; 95% CI 1.80 to 2.05), rural areas (OR: 1.70; 95% CI 1.60 to 1.80), transient ischaemic attack (OR: 1.41; 95% CI 1.30 to 1.54) and hypertension (OR: 1.28; 95% CI 1.19 to 1.38) indicated significantly stronger association with stroke, while family history of CHD (OR: 0.25; 95% CI 0.23 to 0.27), atrial fibrillation (OR: 0.60; 95% CI 0.51 to 0.71), diabetes (OR: 0.76; 95% CI 0.71 to 0.81), dyslipidaemia (OR: 0.76; 95% CI 0.72 to 0.81), smoking (OR: 0.79; 95% CI 0.73 to 0.85) and overweight/obesity (OR: 0.90; 95% CI 0.86 to 0.93) had closer relationship with CHD.

conclusionsThe distribution of risk factors for CHD and stroke were substantial differences. More specific prevention and control measures should be formulated according to the distribution differences of risk factors related to CVD.

Indexed as

Cardiovascular DiseasesCoronary DiseaseStrokeChinaHumansMaleRisk FactorsCardiac EpidemiologyCoronary heart diseaseEPIDEMIOLOGYPUBLIC HEALTHStroke

Identifiers

PMID36424109
PMCPMC9693642

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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.