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. 2024 Sep 23:15:1452664.
doi: 10.3389/fendo.2024.1452664. eCollection 2024.

Association of triglyceride-glucose index with sarcopenia: NHANES 2011-2014

Xue Wei  1 , Dandan Liu  1
Affiliations

Association of triglyceride-glucose index with sarcopenia: NHANES 2011-2014

Xue Wei et al. Front Endocrinol (Lausanne). .

Abstract

Background: A newly developed technique, the Triglyceride-glucose (TyG) index, supplies a more straightforward method to identify IR than the HOMA-IR (Homeostasis Model Assessment of Insulin Resistance). Yet no methodical analysis has looked into the link involving the TyG index and low muscle mass (LMM), low muscle strength (LMS), and sarcopenia within the US. Thus, this study intended to find any connection concerning the TyG index and LMM, LMS, and sarcopenia.

Methods: Between 2011 to 2014, data from the NHANES were used to conduct a nationally representative study involving 2,504 participants. LMM, LMS, and sarcopenia were the outcome variables. Moreover, this positive correlation persists irrespective of age and gender.

Results: The TyG index revealed a significant correlation with the prevalence of developing LMM (OR = 1.63(1.26-2.11), p=0.001), LMS (OR = 1.61(1.36-1.91), p<0.001) and sarcopenia (OR = 1.59 (1.23-2.07), p<0.001), after correcting for all variables. Utilizing smooth curve fitting alongside two-piecewise linear regression models, an inverted U-shaped correlation between the TyG index and the prevalence of LMM, LMS, and sarcopenia. Finally, subgroup analysis revealed that the association between the TyG index and LMM, LMS, and sarcopenia was particularly evident in all gender, age subgroups, and individuals with a normal BMI of 25.

Conclusion: Sarcopenia and the TyG index reveal an essential positive link. It highlights the potential utility of the TyG index as a screening tool for identifying individuals at risk of sarcopenia earlier.

Keywords: TyG index; insulin resistance; low muscle mass; low muscle strength; sarcopenia.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of participants selection.
Figure 2
Figure 2
Smooth curve fitting using GAM to evaluate the nonlinear relationship between the TyG index and the risk of LMM.
Figure 3
Figure 3
Smooth curve fitting using GAM to evaluate the nonlinear relationship between the TyG index and the risk of LMS.
Figure 4
Figure 4
Smooth curve fitting using GAM to evaluate the nonlinear relationship between the TyG index and the risk of Sarcopenia.
See this image and copyright information in PMC

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