Evidence map›Paper›PMID 41824825›Full record

ArticleMedicine2026

Exploring the association between 5 different alternative indicators of insulin resistance and the risk of multiple cardiovascular and metabolic diseases: A cross-sectional NHANES study from 2005 to 2018.

Xiuxia Song, Youfu He, Zhonggui Cai, Lei Peng

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiuxia SongGeneral Family Medicine, Linping Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China.
Youfu HeDepartment of Cardiology, Guizhou Provincial People's Hospital, Guiyang, China.
Zhonggui CaiDepartment of Interventional Cardiology, Shandong Healthcare Group Zao Zhuang Hospital, Zaozhuang, China.
Lei PengDepartment of Cardiology, Linping Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China.ORCID 0009-0002-6190-9296

Funding

Linping District Science and Technology Plan Project LPWJ2024-02-64
6 · The paper itself

Abstract

There is currently an absence of research exploring the correlation between insulin resistance (IR) surrogates and the risk of cardiometabolic multimorbidity (CMM). This study sheds light on the link between different IR surrogates to CMM risk and seeks to identify the optimal surrogate index for IR. Using the National Health and Nutrition Examination Survey 2005 to 2018 data, we applied logistic regression, the Boruta algorithm, trend tests, restricted cubic spline analysis, subgroup analysis, Brier scores, and receiver operating characteristic curve analysis to assess the relationship between CMM risk and IR markers including the triglyceride-glucose index (TyG index), the triglyceride-glucose-body mass index (TyG-BMI index), the metabolic score for insulin resistance (METS-IR), the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C ratio), and homeostasis model assessment of insulin resistance (HOMA-IR). The study included 15,537 participants, of whom 2881 developed CMM. Increased levels of IR markers were significantly associated with a higher CMM risk. Trend analysis showed a dose-response association (P for trend < .05). Restricted cubic spline analysis indicated a J-shaped nonlinear relationship for TyG index and ln[HOMA-IR] with CMM (P for overall < .001, P for nonlinear < .05). Conversely, ln[TyG-BMI], ln[METS-IR], and ln[TG/HDL-C] exhibited linear relationships with CMM (P for overall < .001, P for nonlinear > .05). HOMA-IR showed the highest area under the curve (0.699) for predicting CMM risk. As TyG, TyG-BMI, METS-IR, TG/HDL-C, and HOMA-IR levels increase, the CMM risk increases. Among these, HOMA-IR demonstrates a J-shaped nonlinear relationship with CMM risk and the best predictive performance.

Indexed as

Cardiovascular DiseasesInsulin ResistanceMetabolic DiseasesAdultBiomarkersBlood GlucoseBody Mass IndexCholesterol, HDLCross-Sectional StudiesFemaleHumansMaleMiddle AgedNutrition SurveysRisk FactorsTriglyceridesBiomarkersBlood GlucoseCholesterol, HDLTriglyceridescardiometabolic multimorbidityhomeostasis model assessment of insulin resistanceinsulin resistanceNHANESpredictive model

Identifiers

PMID41824825
PMCPMC12991457

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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.