Evidence map›Paper›PMID 38206625›Full record

ArticleJAMA network open2024

National and Provincial-Level Prevalence and Risk Factors of Carotid Atherosclerosis in Chinese Adults.

Jingzhu Fu, Yuhan Deng, Yuan Ma, Sailimai Man, Xiaochen Yang, Canqing Yu, Jun Lv, Bo Wang, Liming Li

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 3 pooled it
23.7field-weighted citation impact, top 1% 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

55 citing papers in PubMed, 3 syntheses or guidelines pooled it, 59 citations in OpenAlex.

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  18. CD80Cell communication and signaling : CCS · 2026
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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

9 authors at 3 institutions in 1 country.

Jingzhu FuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yuhan DengMeinian Institute of Health, Beijing, China.
Yuan MaMeinian Institute of Health, Beijing, China.
Sailimai ManDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Xiaochen YangMeinian Institute of Health, Beijing, China.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Bo WangMeinian Public Health Institute, Peking University Health Science Center, Beijing, China.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Peking University · CNBeijing Institute of Big Data Research · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Epidemiologic studies on carotid atherosclerosis (CAS) based on nationwide ultrasonography measurements can contribute to understanding the future risk of cardiovascular diseases and identifying high-risk populations, thereby proposing more targeted prevention and treatment measures. Objectives: To estimate the prevalence of CAS within the general population of China and to investigate its distribution among populations with potential risk factors and variation across diverse geographic regions. Design, Setting, and Participants: This multicenter, population-based cross-sectional study used China's largest health check-up chain database to study 10 733 975 individuals aged 20 years or older from all 31 provinces in China who underwent check-ups from January 1, 2017, to June 30, 2022. Main Outcomes and Measures: Carotid atherosclerosis was assessed and graded using ultrasonography as increased carotid intima-media thickness (cIMT), carotid plaque (CP), and carotid stenosis (CS). The overall and stratified prevalences were estimated among the general population and various subpopulations based on demographic characteristics, geographic regions, and cardiovascular disease risk factors. Mixed-effects regression models were used to analyze the risk factors for CAS. Results: Among 10 733 975 Chinese participants (mean [SD] age, 47.7 [13.4] years; 5 861 566 [54.6%] male), the estimated prevalences were 26.2% (95% CI, 25.0%-27.4%) for increased cIMT, 21.0% (95% CI, 19.8%-22.2%) for CP, and 0.56% (95% CI, 0.36%-0.76%) for CS. The prevalence of all CAS grades was higher among older adults (eg, increased cIMT: aged ≥80 years, 92.7%; 95% CI, 92.2%-93.3%), male participants (29.6%; 95% CI, 28.4%-30.7%), those residing in northern China (31.0%; 95% CI, 29.1%-32.9%), and those who had comorbid conditions, such as hypertension (50.8%; 95% CI, 49.7%-51.9%), diabetes (59.0%; 95% CI, 57.8%-60.1%), dyslipidemia (32.1%; 95% CI, 30.8%-33.3%), and metabolic syndrome (31.0%; 95% CI, 29.1%-32.9%). Most cardiovascular disease risk factors were independent risk factors for all CAS stages (eg, hypertension: 1.60 [95% CI, 1.60-1.61] for increased cIMT, 1.62 [95% CI, 1.62-1.63] for CP, and 1.48 [95% CI, 1.45-1.51] for CS). Moreover, the magnitude of the association between several cardiovascular disease risk factors and increased cIMT and CP differed between the sexes and geographic regions. Conclusions and Relevance: These findings suggest that nearly one-quarter of Chinese adults have increased cIMT or CP. The burden of this disease is unevenly distributed across geographic regions and subpopulations and may require different levels of local planning, support, and management. Addressing these disparities is crucial for effectively preventing and managing cardiovascular and cerebrovascular diseases in China.

Indexed as

Cardiovascular DiseasesCarotid Artery DiseasesCarotid StenosisHypertensionAgedCarotid Intima-Media ThicknessChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleMiddle AgedPrevalenceRisk Factors

Identifiers

PMID38206625
PMCPMC10784858
OpenAlexW4390753853

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.