Evidence map›Paper›PMID 40995591›Full record

ArticleFrontiers in endocrinology2025

Relationship between traditional and non-traditional obesity parameters and diabetes and early-onset diabetes: an analysis based on a large cohort.

Miao Luo, Liying Huang, Huan Wang, Lei Zhao

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Miao Luo *Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Liying Huang *Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Huan WangDepartment of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Lei ZhaoDepartment of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetes mellitus (DM), especially early-onset DM, poses a growing global health challenge. While body mass index (BMI) is commonly used to assess obesity, it does not adequately capture fat distribution or metabolic risk. Alternative indices such as waist-to-height ratio (WHtR) and conicity index (CI) may better predict diabetes risk, particularly in younger populations. Methods: This cohort study included 15,453 participants for overall DM risk analysis (mean follow-up: 6.04 years, range: 0.45-12.96) and 5,584 participants under age 40 for early-onset DM (mean follow-up: 3.38 years, range: 0.47-12.32). Ten obesity-related indices were evaluated. Cox regression models estimated the association between each index and the incidence of DM and early-onset DM. Time-dependent receiver operating characteristic (ROC) curves and C-index are used to assess discriminatory performance. Results: During follow-up, 373 cases of DM and 29 cases of early-onset DM were identified. WHtR showed the strongest association with DM risk (HR per SD=1.39; 95% CI: 1.24-1.56), while CI had the strongest association with early-onset DM (HR per SD=2.63; 95% CI: 1.88-3.66). The cardiovascular metabolic index (CMI) had the highest area under the ROC curve (AUC) for assessing short-term DM risk, while lipid accumulation products (LAP) had the highest AUC value for medium- to long-term DM risk. WHtR had the highest AUC of 0.80 in assessing the risk of early-onset DM. Conclusions: Several non-traditional obesity indices, particularly WHtR, CI, CMI, and LAP, are superior to BMI in assessing the risk of DM or early-onset DM. These indices may offer valuable tools for early detection and personalized prevention strategies in clinical practice.

Indexed as

Diabetes MellitusDiabetes Mellitus, Type 2ObesityAdultAge of OnsetBody Mass IndexCohort StudiesFemaleFollow-Up StudiesHumansIncidenceMaleRisk FactorsWaist-Height RatioYoung Adultbody mass indexdiabetesearly-onset diabetesobesityprevention

Identifiers

PMID40995591
PMCPMC12454049

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.