Evidence map›Paper›PMID 39635021›Full record

ArticleThe EPMA journal2024

Changes in the triglyceride-glucose-body mass index estimate the risk of hypertension among the middle-aged and older population: a prospective nationwide cohort study in China in the framework of predictive, preventive, and personalized medicine.

Mingzhu Zhang, Qihua Guan, Zheng Guo, Chaoqun Guan, Xiangqian Jin, Hualei Dong, Shaocan Tang, Haifeng Hou

Abstract read
In one paragraph

Article in The EPMA journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

8 authors.

Mingzhu ZhangSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Qihua GuanSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Zheng GuoDivision of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Vanderbilt Epidemiology Center, Nashville, TN USA.
Chaoqun GuanDepartment of Radiology, Qilu Hospital of Shandong University, Jinan, China.
Xiangqian JinSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.
Hualei DongDepartment of Sanatorium, Shandong Provincial Taishan Hospital, Taian, China.
Shaocan TangDepartment of Rehabilitation Medicine, Shandong Provincial Hospital, 324 Jingwuweiqi Road, Jinan, China.
Haifeng HouSchool of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hypertension is a major modifiable cause of cardiovascular diseases and premature death worldwide. The triglyceride-glucose-body mass index (TyG-BMI), as a novel indicator, has been proposed for assessing hypertension risk. Nevertheless, a paucity of studies has explored the predictive potential of dynamic TyG-BMI for hypertension. The purpose of this study was to investigate whether cumulative TyG-BMI could better predict hypertension incidence and explore the interplay between TyG and BMI in hypertension development. From the perspective of predictive, preventive, and personalized medicine (PPPM/3PM), we assumed that dynamic monitoring of TyG-BMI level and joint assessment of TyG and BMI provide novel insights for individual risk assessment, targeted prevention, and personalized intervention of cardiovascular diseases. Methods: Using data from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide cohort conducted between 2011 and 2018, the changes in TyG-BMI between 2012 and 2015 were categorized into four groups by Results: A total of 2891 participants were enrolled, among whom 386 (13.4%) developed hypertension during a median 36.5-month follow-up period. Logistic regression analysis revealed that, compared to participants with persistently low TyG‑BMI, an increased risk of hypertension was observed among those with a moderate (odds ratio (OR) = 1.60, 95% confidence interval (CI) 1.15 to 2.22), a higher (OR = 1.93, 95% CI 1.28 to 2.89), and the highest TyG‑BMI (OR = 2.33, 95% CI 1.35 to 4.03). A positive linear association of cumulative TyG-BMI with hypertension was discovered ( Conclusions: This study demonstrated a significant positive association between dynamic TyG-BMI and hypertension among the Chinese middle-aged and older population. In the context of PPPM/3PM, long-term monitoring of TyG-BMI could assist in identifying individuals at high risk of hypertension, strengthening primary prevention efforts and facilitating prompt intervention strategies. In addition, this study revealed the mutual effect of TyG and BMI on hypertension development, which provides a novel approach for mitigating the risk of cardiovascular diseases via addressing metabolic disorders, thereby enhancing effective prevention and targeted intervention. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00380-6.

Indexed as

BMICHARLS cohortHypertensionLong‑term changesMetabolic disorderMonitoringPredictive, preventive, and personalized medicine (PPPM / 3PM)Risk assessmentRisk mitigationTargeted interventionTriglyceride-glucose–body mass index

Identifiers

PMID39635021
PMCPMC11612070

What OpenQuestion holds

Textmetadata
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.