Evidence map›Paper›PMID 38402161›Full record

ArticleCardiovascular diabetology2024

Link between triglyceride-glucose-body mass index and future stroke risk in middle-aged and elderly chinese: a nationwide prospective cohort study.

Yuankai Shao, Haofei Hu, Qiming Li, Changchun Cao, Dehong Liu, Yong Han

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 83 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 2 pooled it
40.6field-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

83 citing papers in PubMed, 2 syntheses or guidelines pooled it, 101 citations in OpenAlex.

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23 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

6 authors at 1 institution in 1 country.

Yuankai Shao *Department of Emergency, Shenzhen Second People's Hospital,The First Affiliated Hospital of Shenzhen University, No. 3002 Sungang Road, Futian District, Shenzhen, 518035, Guangdong, China.
Haofei Hu *Department of Nephrology, Shenzhen Second People's Hospital, Shenzhen, 518035, Guangdong, China.
Qiming Li *Department of Emergency, Shenzhen Second People's Hospital,The First Affiliated Hospital of Shenzhen University, No. 3002 Sungang Road, Futian District, Shenzhen, 518035, Guangdong, China.
Changchun Cao *Department of Rehabilitation, Shenzhen Dapeng New District Nan'ao People's Hospital, Shenzhen, 518000, Guangdong, China.
Dehong LiuDepartment of Emergency, Shenzhen Second People's Hospital,The First Affiliated Hospital of Shenzhen University, No. 3002 Sungang Road, Futian District, Shenzhen, 518035, Guangdong, China. dhliu_emergency@163.com.
Yong HanDepartment of Emergency, Shenzhen Second People's Hospital,The First Affiliated Hospital of Shenzhen University, No. 3002 Sungang Road, Futian District, Shenzhen, 518035, Guangdong, China. Hanyong511023@163.com.
Shenzhen Second People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCurrent literature is deficient in robust evidence delineating the correlation between the triglyceride glucose-body mass index (TyG-BMI) and the incidence of stroke. Consequently, this investigation seeks to elucidate the potential link between TyG-BMI and stroke risk in a cohort of middle-aged and senior Chinese individuals.

methodsThis study employs longitudinal data from four waves of the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, 2013, 2015, and 2018, encompassing 8,698 participants. The CHARLS cohort was assembled using a multistage probability sampling technique. Participants underwent comprehensive evaluations through standardized questionnaires administered via face-to-face interviews. Our analytic strategy involved the application of Cox proportional hazards regression models to investigate the association between TyG-BMI and the risk of stroke. To discern potential non-linear relationships, we incorporated Cox proportional hazards regression with smooth curve fitting. Additionally, we executed a battery of sensitivity and subgroup analyses to validate the robustness of our findings.

resultsOur study utilized a multivariate Cox proportional hazards regression model and found a significant correlation between the TyG-BMI and the risk of stroke. Specifically, a 10-unit increase in TyG-BMI corresponded to a 4.9% heightened risk of stroke (HR = 1.049, 95% CI 1.029-1.069). The analysis also uncovered a non-linear pattern in this relationship, pinpointed by an inflection point at a TyG-BMI value of 174.63. To the left of this inflection point-meaning at lower TyG-BMI values-a 10-unit hike in TyG-BMI was linked to a more substantial 14.4% rise in stroke risk (HR 1.144; 95% CI 1.044-1.253). Conversely, to the right of the inflection point-at higher TyG-BMI values-each 10-unit increment was associated with a smaller, 3.8% increase in the risk of stroke (HR 1.038; 95% CI 1.016-1.061).

conclusionsIn the middle-aged and elderly Chinese population, elevated TyG-BMI was significantly and positively associated with stroke risk. In addition, there was also a specific non-linear association between TyG-BMI and stroke (inflection point 174.63). Further reduction of TyG-BMI below 174.63 through lifestyle changes and dietary control can significantly reduce the risk of stroke.

Indexed as

GlucoseStrokeAgedBiomarkersBlood GlucoseBody Mass IndexChinaHumansLongitudinal StudiesMiddle AgedProspective StudiesRisk FactorsTriglyceridesBiomarkersBlood GlucoseGlucoseTriglyceridesInsulin resistanceNon-linear associationSmooth curve fittingStrokeTriglyceride glucose-body mass index

Identifiers

PMID38402161
PMCPMC10893757
OpenAlexW4392129572

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.