Evidence map›Paper›PMID 38184598›Full record

ArticleCardiovascular diabetology2024

The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003-2018.

Keke Dang, Xuanyang Wang, Jinxia Hu, Yuntao Zhang, Licheng Cheng, Xiang Qi, Lin Liu, Zhu Ming, Xinmiao Tao, Ying Li

Open access · goldAbstract read
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 477 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
477citing papers in PubMed, 2 pooled it
173.5field-weighted citation impact, top 1% of its field
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

477 citing papers in PubMed, 2 syntheses or guidelines pooled it, 485 citations in OpenAlex.

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417 more citing papers are in PubMed but not listed here.

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

10 authors at 2 institutions in 1 country.

Keke Dang *Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xuanyang Wang *Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Jinxia HuDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Yuntao ZhangMED-X Institute, Center for Immunological and Metabolic Diseases (CIMD), First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710000, China.
Licheng ChengDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xiang QiDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Lin LiuDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Zhu MingDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Xinmiao TaoDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China.
Ying LiDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, 157 Baojian Road, Heilongjiang, 150081, People's Republic of China. liying_helen@163.com.
Harbin Medical University · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

National Natural Science Foundation of China 82030100
6 · The paper itself

Abstract

backgroundIn the American population, the relationship between the triglyceride-glucose (TyG) index and TYG combined with indicators of obesity and cardiovascular disease (CVD) and its mortality has been less well studied.

methodsThis cross-sectional study included 11,937 adults from the National Health and Nutrition Examination Survey (NHANES) 2003-2018. Cox proportional hazards model, binary logistic regression analyses, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were used to analyze the relationship between TyG and its combined obesity-related indicators and CVD and its mortality. Mediation analysis explored the mediating role of glycated hemoglobin and insulin in the above relationships.

resultsIn this study, except for no significant association between TyG and CVD mortality, TyG, TyG-WC, TyG-WHtR, and TyG-BMI were significantly and positively associated with CVD and CVD mortality. TyG-WHtR is the strongest predictor of CVD mortality (HR 1.66, 95% CI 1.21-2.29). The TyG index correlated better with the risk of coronary heart disease (OR 2.52, 95% CI 1.66-3.83). TyG-WC correlated best with total CVD (OR 2.37, 95% CI 1.77-3.17), congestive heart failure (OR 2.14, 95% CI 1.31-3.51), and angina pectoris (OR 2.38, 95% CI 1.43-3.97). TyG-WHtR correlated best with myocardial infarction (OR 2.24, 95% CI 1.45-3.44). RCS analyses showed that most of the above relationships were linear (P-overall < 0.0001, P-nonlinear > 0.05). Otherwise, ROC curves showed that TyG-WHtR and TyG-WC had more robust diagnostic efficacy than TyG. In mediation analyses, glycated hemoglobin mediated in all the above relationships and insulin-mediated in partial relationships.

conclusionsTyG-WC and TyG-WtHR enhance CVD mortality prediction, diagnostic efficacy of CVD and its mortality, and correlation with some CVD over and above the current hottest TyG. TyG-WC and TyG-WtHR are expected to become more effective metrics for identifying populations at early risk of cardiovascular disease and improve risk stratification.

Indexed as

Cardiovascular DiseasesAdultCross-Sectional StudiesGlucoseGlycated HemoglobinHumansInsulinNutrition SurveysObesityTriglyceridesGlucoseGlycated HemoglobinInsulinTriglyceridesCardiovascular diseaseCardiovascular disease (CVD) mortalityNational Health and Nutrition Examination Survey (NHANES)Triglyceride glucose-body mass index (TyG-BMI)Triglyceride glucose (TyG)Triglyceride glucose-waist circumference (TyG-WC)Triglyceride glucose-waist height ratio (TyG-WHtR)

Identifiers

PMID38184598
PMCPMC10771672
OpenAlexW4390640401

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.