Evidence mapPaperPMID 38934874Full record

ArticleJournal of the American Heart Association2024

Urinary Equol and Equol-Predicting Microbial Species Are Favorably Associated With Cardiometabolic Risk Markers in Chinese Adults.

Shaoxian Liang, Honghua Zhang, Yufeng Mo, Yamin Li, Xiaoyu Zhang, Hongjuan Cao, Shaoyu Xie, Danni Wang, Yaning Lv, Yaqin Wu and 2 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. (Poly)phenol-gut microbiota interactions and their impact on human health.Current opinion in clinical nutrition and metabolic care · 2025
    Review
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Review
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

12 authors.

Shaoxian LiangDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0009-0002-8053-256X
Honghua ZhangDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0009-0003-2447-442X
Yufeng MoDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0009-0004-5086-4867
Yamin LiDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0009-0001-7647-9121
Xiaoyu ZhangDepartment of Physical Examination Center The First Affiliated Hospital of Anhui Medical University Hefei Anhui China.ORCID 0009-0000-5999-9566
Hongjuan CaoDepartment of Chronic Noncommunicable Diseases Prevention and Control Lu'an Municipal Center for Disease Control and Prevention Lu'an Anhui China.ORCID 0009-0004-1664-289X
Shaoyu XieDepartment of Chronic Noncommunicable Diseases Prevention and Control Lu'an Municipal Center for Disease Control and Prevention Lu'an Anhui China.ORCID 0009-0008-7959-8215
Danni WangDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0000-0002-1273-8403
Yaning LvTechnology Center of Hefei Customs, and Anhui Province Key Laboratory of Analysis and Detection for Food Safety Hefei Anhui China.ORCID 0009-0003-0654-309X
Yaqin WuTechnology Center of Hefei Customs, and Anhui Province Key Laboratory of Analysis and Detection for Food Safety Hefei Anhui China.ORCID 0009-0001-7488-0720
Zhuang ZhangDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0009-0004-1144-9740
Wanshui YangDepartment of Nutrition, Center for Big Data and Population Health of IHM School of Public Health, Anhui Medical University Hefei Anhui China.ORCID 0000-0002-7365-2689

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe association between soy isoflavones intake and cardiometabolic health remains inconclusive. We investigated the associations of urinary biomarkers of isoflavones including daidzein, glycitein, genistein, equol (a gut microbial metabolite of daidzein), and equol-predicting microbial species with cardiometabolic risk markers. METHODS AND

resultsIn a 1-year study of 305 Chinese community-dwelling adults aged ≥18 years, urinary isoflavones, fecal microbiota, blood pressure, blood glucose and lipids, and anthropometric data were measured twice, 1 year apart. Brachial-ankle pulse wave velocity was also measured after 1 year. A linear mixed-effects model was used to analyze repeated measurements. Logistic regression was used to calculate the adjusted odds ratio (aOR) and 95% CI for the associations for arterial stiffness. Each 1 μg/g creatinine increase in urinary equol concentrations was associated with 1.47%, 0.96%, and 3.32% decrease in triglycerides, plasma atherogenic index, and metabolic syndrome score, respectively (all

conclusionsOur findings suggest that urinary equol and equol-predicting microbial species may improve cardiometabolic risk parameters in Chinese adults.

Indexed as

BiomarkersCardiometabolic Risk FactorsEquolGastrointestinal MicrobiomeVascular StiffnessAdultCardiovascular DiseasesChinaEast Asian PeopleFecesFemaleHumansIsoflavonesMaleMiddle AgedRisk AssessmentBiomarkersEquolIsoflavonescardiometabolic riskequolgut microbiomeisoflavonesrepeated measurements

Identifiers

PMID38934874
PMCPMC11255694

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.