Evidence map›Paper›PMID 39021592›Full record

ArticleFrontiers in nutrition2024

Triglyceride glucose-related indexes and lipid accumulation products-reliable markers of insulin resistance in the Chinese population.

Lei Liu, Yufang Luo, Min Liu, Chenyi Tang, Hong Liu, Guo Feng, Meng Wang, Jinru Wu, Wei Zhang

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Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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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

23 citing papers in PubMed, 1 synthesis or guideline 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

9 authors.

Lei Liu *Health Management Center, The Third Xiangya Hospital of Central South University, Changsha, China.
Yufang Luo *Department of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Min LiuDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Chenyi TangDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Hong LiuDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Guo FengDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Meng WangDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Jinru WuDepartment of Clinical Nutrition, The Third Xiangya Hospital of Central South University, Changsha, China.
Wei ZhangDepartment of Clinical Nutrition, Hunan Aerospace Hospital, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Insulin resistance (IR) is a pivotal pathogenic component of metabolic diseases. It is crucial to identify convenient and reliable indicators of insulin resistance for its early detection. This study aimed at assessing the predictive ability of seven novel obesity and lipid-related indices. Methods: A total of 5,847 female and 3,532 male healthy subjects were included in the study. The triglyceride glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), lipid accumulation products (LAP), body roundness index (BRI), body adiposity index (BAI), and visceral adiposity index (VAI) were measured and calculated using the established formulae. IR was diagnosed using the homeostatic model assessment of insulin resistance (HOMA-IR) index over the third quantile. Results: The levels of all seven lipid-related indices were significantly higher in subjects with higher HOMA-IR values than in those with lower HOMA-IR values. These indices displayed moderate to high effectiveness [receiver operating characteristic (ROC) curve-area under the curve (AUC) > 0.6] in predicting IR. Among them, TyG-BMI (AUC: 0.729), LAP (AUC: 0.708), and TyG-WC (AUC: 0.698) showed the strongest association with HOMA-IR. In the female population, the AUC for TyG-BMI, LAP, and TyG-WC in predicting IR was 0.732, 0.705, and 0.718, respectively. Logistic regression analysis showed the optimal cut-off values of those indicators in predicting IR as follows: TyG-BMI: male subjects - 115.16 [odds ratio (OR) = 6.05, 95% CI: 5.09-7.19], female subjects - 101.58 (OR = 4.55, 95% CI: 4.00-5.16); LAP: male subjects - 25.99 (OR = 4.53, 95% CI: 3.82-5.38), female subjects - 16.11 (OR = 3.65, 95% CI: 3.22-4.14); and TyG-WC: male subjects - 409.43 (OR = 5.23, 95% CI: 4.48-6.24), female subjects - 342.48 (OR = 4.07, 95% CI: 3.59-4.61). Conclusion: TyG-index-related parameters and LAP appear to be effective predictors of IR in the Chinese population. Specifically, TyG-BMI may be the most appropriate predictor of IR.

Indexed as

HOMA-IRinsulin resistancelipid accumulation productslipid-related indicestriglyceride glucose-related indexes

Identifiers

PMID39021592
PMCPMC11253805

What Socratic holds

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LicenceCC BY
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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 Socratic graph.