Evidence map›Paper›PMID 39030624›Full record

ArticleLipids in health and disease2024

The association between the triglyceride-glucose index and sarcopenia: data from the NHANES 2011-2018.

Jiju Yang, Cong Liu, Sihao Zhao, Lixiang Wang, Guanwei Wu, Ziyi Zhao, Chungen Li

Abstract read
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Article in Lipids in health and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 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

38 citing papers in PubMed, 3 syntheses or guidelines 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

7 authors.

Jiju Yang *Beijing University of Chinese Medicine, Beijing, China.
Cong Liu *Beijing University of Chinese Medicine, Beijing, China.
Sihao ZhaoBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.
Lixiang WangBeijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.
Guanwei WuBeijing University of Chinese Medicine, Beijing, China.
Ziyi Zhao *Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China. zhaoziyi@hotmail.com.
Chungen Li *Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China. leechungen@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Triglyceride-glucose (TyG) index is a marker of insulin resistance, but its role in sarcopenia is controversial. The purpose of this study was to investigate the association of the TyG index with sarcopenia.

methods4030 participants aged 20 years and above were selected from National Health and Nutrition Examination Survey for cross sectional study. Weighted logistic regression model was used to estimate the association between TyG index and sarcopenia. Threshold effect analysis and restricted cubic spline were employed to describe nonlinear link, with interaction tests and subgroup analyses performed.

resultsIt was found in the fully adjusted model that the TyG index was positively associated with sarcopenia (per 1-unit increase in the TyG index: OR = 1.31, 95%CI: 1.07, 1.60). This association was further highlighted in groups characterized by the absence of MetS or diabetes, as well as the absence of vigorous or moderate work activity. Furthermore, analysis of the curve fitting and threshold effects indicated a nonlinear relationship, which exhibited a turning point at 9.14.

conclusionThe study results indicated that the TyG index was positively associated with sarcopenia. Enhancing the management of insulin resistance could help reduce the risk of developing sarcopenia.

Indexed as

Blood GlucoseInsulin ResistanceNutrition SurveysSarcopeniaTriglyceridesAdultAgedCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedBlood GlucoseTriglyceridesCross-sectional studyInsulin resistanceNHANESSarcopeniaTriglyceride-glucose index

Identifiers

PMID39030624
PMCPMC11264742

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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.