Evidence map›Paper›PMID 37936651›Full record

ArticleEClinicalMedicine2023

Ranking age-specific modifiable risk factors for cardiovascular disease and mortality: evidence from a population-based longitudinal study.

Fei Tian, Lan Chen, Zhengmin Min Qian, Hui Xia, Zilong Zhang, Jingyi Zhang, Chongjian Wang, Michael G Vaughn, Maya Tabet, Hualiang Lin

Open access · goldAbstract read
In one paragraph

Article in EClinicalMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 4 pooled it
18.2field-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

70 citing papers in PubMed, 4 syntheses or guidelines pooled it, 83 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review

10 more citing papers are in PubMed but not listed here.

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

10 authors at 4 institutions in 2 countries.

Fei TianDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Lan ChenDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Zhengmin Min QianDepartment of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA.
Hui XiaCenter for Health Care, Longhua District, Shenzhen, China.
Zilong ZhangDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Jingyi ZhangDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Chongjian WangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, 450001, China.
Michael G VaughnSchool of Social Work, Saint Louis University, Saint Louis, MO, 63103, USA.
Maya TabetCollege of Global Population Health, University of Health Sciences and Pharmacy in St. Louis, 1 Pharmacy Place, St. Louis, MO, 63110, USA.
Hualiang LinDepartment of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
Sun Yat-sen University · CNSaint Louis University · USUniversity of Health Sciences and Pharmacy · USZhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular disease (CVD) remains a paramount contemporary health challenge. This study examined age-specific effects of 14 risk factors on CVD and mortality in different age groups. Methods: We analyzed data from 226,759 CVD-free participants aged 40 years and older in the UK Biobank during the period from baseline time (2006-2010) to September 30, 2021. The primary CVD outcome was a composite of incident coronary artery disease, heart failure, and stroke. We calculated age-specific hazard ratios (HRs) and population-attributable fractions (PAF) for CVD and mortality associated with 14 potentially modifiable risk factors. Findings: During 12.17-year follow-up, 23,838 incident CVD cases and 11,949 deaths occurred. Age-specific disparities were observed in the risk factors contributing to CVD, and the overall PAF declined with age (PAF of 56.53% in middle-age; 49.78% in quinquagenarian; 42.45% in the elderly). Metabolic factors had the highest PAF in each age group, with hypertension (14.04% of the PAF) and abdominal obesity (9.58% of the PAF) being prominent. Behavioral factors had the highest PAF in the middle-aged group (10.68% of the PAF), and smoking was the leading behavioral factor in all age groups. In socioeconomic and psychosocial risk clusters, low income contributed most among middle-aged (3.74% of the PAF) and elderly groups (3.66% of the PAF), while less education accounted more PAF for quinquagenarian group (4.46% of the PAF). Similar age-specific patterns were observed for cardiovascular subtypes and mortality. Interpretation: A large fraction of CVD cases and deaths were associated with modifiable risk factors in all age groups. Targeted efforts should focus on the most impactful risk factors, as well as age-specific modifiable risk factors. These findings may inform the development of more precise medical strategies to prevent and manage CVD and related mortality. Funding: The work was supported by the Bill & Melinda Gates Foundation (grant number: INV-016826 to Hualiang Lin) and the National Natural Science Foundation of China (grant number: 82373534 to Hualiang Lin).

Indexed as

AgeCardiovascular diseaseEpidemiologyModifiable factorProspective study

Identifiers

PMID37936651
PMCPMC10626167
OpenAlexW4387101227

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.