Evidence map›Paper›PMID 40235662›Full record

ArticleFrontiers in endocrinology2025

Associations of obesity and novel lipid indicators in the risk of type 2 diabetes mellitus in Chinese elderly hypertensive patients.

Xihui Jin, Yushuang Wei, YeMei Mo, Qiuling Zhang, Mingjie Xu, Xiaoyou Mai, Boteng Yan, Wenchao Xie, Shengzhu Huang, Mingli Li and 1 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

11 authors.

Xihui Jin *Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, Guangxi, China.
Yushuang Wei *Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
YeMei Mo *The First People's Hospital of Yulin, Yulin, Guangxi, China.
Qiuling ZhangThe First People's Hospital of Yulin, Yulin, Guangxi, China.
Mingjie XuInstitute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, Guangxi, China.
Xiaoyou MaiCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
Boteng YanInstitute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, Guangxi, China.
Wenchao XieThe First People's Hospital of Yulin, Yulin, Guangxi, China.
Shengzhu HuangCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
Mingli LiCenter for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
Zengnan MoInstitute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The associations of waist circumference (WC), body mass index (BMI), lipid accumulation product (LAP), Chinese visceral adiposity index (CVAI), and triglyceride-glucose Index (TyG) with the risk of type 2 diabetes mellitus (T2DM) remained uncertain in Chinese middle-aged and elderly hypertensive patients. Methods: A total of 1,965 hypertensive participants aged 45 years and elderly were included in the cross-sectional analysis, and 1,576 hypertensive participants without T2DM for the cohort analysis. In the cross-sectional study, binary logistic regression, restricted cubic splines (RCS), and receiver operating characteristic (ROC) were used to analyze the relationships between WC, BMI, LAP, CVAI, and TyG with and T2DM in hypertensive patients. In the cohort study, Kaplan-Meier survival analyses and Cox regression were further performed to determine the associations of these indicators with incident T2DM risk. Results: In the cohort study, there were 101 incident T2DM cases occurred during a median follow-up of 30 months, with an incident rate was 2.78 per 100 person-years. The cross-sectional study showed that the risk of T2DM increased significantly with higher quartiles of WC, BMI, LAP, CVAI, and TyG (all Conclusion: Higher levels of WC, BMI, LAP, CVAI, and TyG are associated with a higher riskof developing incident T2DM in Chinese elderly hypertensive patients, and TyG might be the most effective predictive indicator.

Indexed as

Diabetes Mellitus, Type 2HypertensionLipidsObesityAgedBody Mass IndexChinaCohort StudiesCross-Sectional StudiesEast Asian PeopleFemaleFollow-Up StudiesHumansLipid Accumulation ProductMaleMiddle AgedLipidsTriglyceridesChinese communityelderly hypertensive patientsnovel lipid indicatorsobesity indicestype 2 diabetes mellitus

Identifiers

PMID40235662
PMCPMC11996637

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Registered trials

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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.