Evidence map›Paper›PMID 40189520›Full record

ArticleBMC medicine2025

Associations between education and ideal cardiovascular health metrics across 36 low- and middle-income countries.

Yi Zhang, Guangyu Tong, Ning Ma, Shaoru Chen, Yuhao Kong, Lhuri Dwianti Rahmartani, Justice Moses K Aheto, Andrew Marvin Kanyike, Pengyang Fan, Md Ashfikur Rahman and 12 more

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

22 authors.

Yi ZhangVanke School of Public Health, Tsinghua University, Beijing, China.
Guangyu TongDepartment of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Ning MaVanke School of Public Health, Tsinghua University, Beijing, China.
Shaoru ChenVanke School of Public Health, Tsinghua University, Beijing, China.
Yuhao KongVanke School of Public Health, Tsinghua University, Beijing, China.
Lhuri Dwianti RahmartaniDepartment of Epidemiology, Faculty of Public Health, Universitas Indonesia, Depok, Jawa Barat, Indonesia.
Justice Moses K AhetoDepartment of Biostatistics, School of Public Health, University of Ghana, Accra, Ghana.
Andrew Marvin KanyikeFaculty of Health Sciences, Busitema University, Mbale, Uganda.
Pengyang FanVanke School of Public Health, Tsinghua University, Beijing, China.
Md Ashfikur RahmanDevelopment Studies Discipline, Khulna University, Khulna, 9208, Bangladesh.
Abdallah MkopiIfakara Health Institute, Dar Es Salaam, Tanzania.
Rockli KimInterdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea.
Peter KaroliNational Institute for Medical Research, Dar Es Salaam, Tanzania.
John Lapah NiyiGhana Health Service, Gushegu Municipal Health Directorate, Gushegu, Ghana.
Melkamu Aderajew ZemeneDepartment of Public Health, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia.
Lin ZhangThe School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Feng ChengVanke School of Public Health, Tsinghua University, Beijing, China.
Chunling LuDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA.
S V SubramanianDepartment of Social and Behavioral Sciences, Harvard TH Chan School of Public Health, Boston, MA, USA.
Pascal GeldsetzerDivision of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Yue QiuInstitute for Hospital Management, Tsinghua University, Beijing, China. qiuyue8965@tsinghua.edu.cn.
Zhihui LiVanke School of Public Health, Tsinghua University, Beijing, China. zhihuili@tsinghua.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe relationship between education and cardiovascular health (CVH) metrics in low- and middle-income countries (LMICs) remains unclear. This study explores the associations between education and ideal cardiovascular health score (CVHS), as well as seven CVH metrics.

methodsThis cross-sectional study extracted data from the STEPwise approach to surveillance surveys in 36 LMICs between 2010 and 2020. We assessed CVHS using the sum score in seven metrics defined by American Heart Association: (1) ≥ 150 min/week of moderate, or 75 min/week of vigorous activity, or an equivalent combination; (2) BMI < 25 kg/m

resultsAmong 81,327 adult participants, the overall ideal CVHS prevalence for the studied countries was highest among individuals with primary education (52.9%, 95% CI: 51.0-54.9), surpassing those of other education levels - 48.0% (95% CI: 44.6-51.3, P = 0.003) for those with no education and 39.1% (95% CI: 36.5-41.8, P < 0.001) for those with tertiary education. Five (ideal physical activity, BMI, blood pressure, total cholesterol, and blood glucose) in seven CVH metrics peaked among participants with primary or secondary education. For instance, the prevalence of ideal blood pressure among individuals with primary education was 34.4% (95% CI: 32.7-36.1), higher than the prevalence in other education levels, ranging from 28.6% to 32.3%. These patterns were concentrated in low-income countries and lower-middle-income countries, while in upper-middle-income countries, the prevalence of ideal CVHS increased with higher education levels, ranging from 15.4% for individuals with no education to 33.1% for those with tertiary education.

conclusionsIn LMICs, the association between education and ideal CVHS, along with several CVH metrics, exhibited un inverted U-shape, which may be closely related to the different stages of epidemiologic transition.

Indexed as

Cardiovascular DiseasesDeveloping CountriesEducational StatusAdultBlood PressureCross-Sectional StudiesFemaleHumansMaleMiddle AgedYoung AdultEducationIdeal cardiovascular health metricsIdeal cardiovascular health scoreInverted U-shapeLow- and middle-income countries

Identifiers

PMID40189520
PMCPMC11974039

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LicenceCC BY-NC-ND
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Registered trials

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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.