Evidence map›Paper›PMID 41079004›Full record

ArticleEuropean heart journal open2025

Contrasting associations of blood lipids with risk of myocardial infarction in Chinese and European adults.

Hanyu Wang, Robert Clarke, Christiana Kartsonaki, Iona Millwood, Robin Walters, Michael Hill, Daniel Avery, Canqing Yu, DianJian-Yi Sun, Jun Lv and 5 more

Abstract read
In one paragraph

Article in European heart journal open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

15 authors.

Hanyu WangClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Robert ClarkeClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.ORCID https://orcid.org/0000-0002-9802-8241
Christiana KartsonakiClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Iona MillwoodClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Robin WaltersClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Michael HillClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Daniel AveryClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.ORCID https://orcid.org/0000-0002-0019-0014
DianJian-Yi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.
Shanpeng LiQingdao Centre for Disease Control, Qindao, Shandong 266033, China.
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.
Zhengming ChenClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.ORCID https://orcid.org/0000-0001-6423-105X
Neil WrightClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.
Derrick A BennettClinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Roosevelt Drive, Oxford OX3 7LF, UK.ORCID https://orcid.org/0000-0002-9170-8447

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Little is known about the importance of blood lipids for risk of myocardial infarction (MI) in Chinese vs. European populations. We compared the associations with MI of apolioprotein B (ApoB) vs. low-density lipoprotein cholesterol (LDL-C) and remnant-cholesterol (remnant-C) vs. triglycerides in the China Kadoorie Biobank (CKB) and UK Biobank (UKB). Methods and results: Plasma levels of LDL-C, high-density lipoprotein-cholesterol (HDL-C), apolipoprotein B (ApoB), apolipoprotein A1 (ApoA1), non-HDL-C, remnant-C, LDL-C/ApoB, and HDL-C/ApoA1 ratios were measured in a nested case-control study of MI (948 cases, 6101 controls) in CKB and a prospective study (5344 cases in 279 989 participants) in UKB. Associations of lipids with MI were assessed using logistic regression in CKB and Cox regression in UKB after adjustment for confounders and correction for regression dilution. The mean levels of LDL-C were about 30% lower in CKB than in UKB [2.3 (0.6) vs. 3.7 (0.8) mmol/L], but mean levels of HDL-C were comparable [1.3 (0.3) vs. 1.5 (0.4) mmol/L], as were those for triglycerides [1.8 (1.1) vs. 1.7 (1.1) mmol/L]. While the rate ratios (RRs) of MI for 1 SD higher usual levels of LDL-C in Chinese were about half those in Europeans (1.27; 1.13-1.44 vs. 1.55; 1.49-1.61), the corresponding RRs for ApoB or non-HDL with MI were comparable between Chinese and Europeans. Conclusion: The findings reinforce current guidelines for primary prevention of atherosclerotic cardiovascular disease (ASCVD) in China that advocate initiation of statin treatment in individuals at high-risk of ASCVD rather than high levels of LDL-C.

Indexed as

Blood lipidsChinese and European populationsMyocardial infarction

Identifiers

PMID41079004
PMCPMC12514723

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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.