Evidence map›Paper›PMID 41033739›Full record

ArticleJournal of the American College of Cardiology2025

Very High Prevalence of Nonoptimally Controlled Traditional Risk Factors at the Onset of Cardiovascular Disease.

Hokyou Lee, Xiaoning Huang, Sadiya S Khan, Dasom Son, Hyeok-Hee Lee, Eun-Jin Kim, Donald M Lloyd-Jones, Hyeon Chang Kim, Philip Greenland

Abstract read
In one paragraph

Article in Journal of the American College of Cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. How much does eliminating one or two cardiovascular risk factors matter?: Evidence from the Global Cardiovascular Risk Consortium.European heart journal supplements : journal of the European Society of Cardiology · 2026
    Article
  5. Article
  6. [Prevention and prophylaxis in angiology].Innere Medizin (Heidelberg, Germany) · 2026
    Article
  7. Review
  8. 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

9 authors.

Hokyou LeeDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea; Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Korea. Electronic address: hokyou.lee@yuhs.ac.
Xiaoning HuangDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Sadiya S KhanDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Dasom SonDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.
Hyeok-Hee LeeDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea; Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
Eun-Jin KimDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.
Donald M Lloyd-JonesDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Hyeon Chang KimDepartment of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea; Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Korea.
Philip GreenlandDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.

Funding

Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Task Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 to 2025
$5.1M
TO EXERCISE OPTION PERIOD ONE (1) FOR TASK AREA A - MESA CORE OPERATIONS, FIELD CENTER.75N92020D00004 · NHLBI · NORTHWESTERN UNIVERSITY · PI SIEGEL, JONATHAN H · 2020 to 2025
$4.5M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00006 · NHLBI · UNIVERSITY OF MINNESOTA · PI PANKOW, JAMES S · 2020 to 2025
$4.4M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00003 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI POST, WENDY S · 2020 to 2025
$3.8M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00007 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI BERTONI, ALAIN GERALD · 2020 to 2025
$3.5M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00002 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHEA, STEVEN J · 2020 to 2025
$3.4M
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095166 · HC · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI TRACY, RUSSELL P · 1999 to 2001
$758k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC095162 · HC · JOHNS HOPKINS UNIVERSITY · PI SZKLO, MOYSES A · 1999 to 2000
$694k
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169
6 · The paper itself

Abstract

backgroundRecent studies suggest that coronary heart disease (CHD) may frequently occur in the absence of traditional cardiovascular disease (CVD) risk factors. However, it is unclear whether this could reflect missed clinical diagnoses or subthreshold nonoptimal risk factor exposure preceding CHD, and whether similar patterns are observed for heart failure (HF) or stroke.

objectivesThe purpose of this study was to determine the antecedent occurrence of nonoptimal levels of 4 traditional risk factors (blood pressure [BP], cholesterol, glucose, and tobacco smoking) before first CHD, HF, or stroke.

methodsWe analyzed 2 population-based prospective cohorts: KNHIS (Korean National Health Insurance Service) (n = 9,341,100; baseline age ≥20 years; follow-up, 2009-2022) and MESA (Multi-Ethnic Study of Atherosclerosis) (n = 6,803; baseline age 45-84 years; follow-up, 2000-2019). Among individuals who developed incident CHD, HF, or stroke during follow-up, we determined the prevalence of ≥1 traditional risk factor above optimal level-systolic BP ≥120 mm Hg or diastolic BP ≥80 mm Hg or BP-lowering treatment; total cholesterol ≥200 mg/dL or lipid-lowering treatment; fasting glucose ≥100 mg/dL or diagnosis of diabetes or glucose-lowering treatment; or past or current smoking-at any visit before CVD.

resultsAnalyses were based on 601,025 and 1,188 CVD events in KNHIS and MESA, respectively. Prevalence of ≥1 nonoptimal risk factor was high (99.7% and 99.6%) before CHD, with similar patterns before HF (99.4% and 99.5%) and stroke (99.3% and 99.5%) in both KNHIS and MESA, respectively. Prevalence of ≥1 risk factor before CVD was consistently high (>99%) across age groups in both men and women, with the lowest proportion observed for HF and stroke (>95%) when occurring at ages <60 years in women. Prevalence of ≥2 risk factors was also common (93.2% to 97.2%) before CVD events.

conclusionsIn this binational study of 2 prospective cohorts, the presence of nonoptimal levels of ≥1 traditional risk factor was nearly universal before CVD. These results not only challenge claims that CHD events frequently occur without antecedent major risk factors but also demonstrate that other CVD events, including HF or stroke, rarely occur in the absence of nonoptimal traditional risk factors, highlighting the importance of primordial prevention efforts.

Indexed as

Cardiovascular DiseasesAgedAged, 80 and overBlood GlucoseBlood PressureCholesterolFemaleFollow-Up StudiesHeart Disease Risk FactorsHeart FailureHumansMaleMiddle AgedPrevalenceProspective StudiesRepublic of KoreaBlood GlucoseCholesterolcardiovascular diseasecardiovascular healthprimordial preventiontraditional risk factors

Identifiers

PMID41033739
PMCPMC13519508

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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.