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ORIGINAL RESEARCH

Association of Non-Insulin-Based Insulin Resistance Indices with Risk of Incident Prediabetes and Diabetes in a Chinese Rural Population: A 12-Year Prospective Study

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Pages 3809-3819 | Received 11 Aug 2022, Accepted 06 Dec 2022, Published online: 12 Dec 2022
 

Abstract

Objective

Three non-insulin-based insulin resistance (IR) indices, ie, triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for IR (METS-IR), were considered powerful and simplified alternatives for IR. However, evidence for the association between the three IR indices and incident type 2 diabetes mellitus (T2DM), especially impaired fasting glucose (IFG), remains limited. Therefore, this study aimed to explore the association among IR indices, incident IFG, and T2DM in a rural population cohort.

Methods

We analyzed data from 2209 adults (aged 24–75 years) at baseline and from 1205 normoglycemic participants who were followed up. Cox proportional hazards models were used to evaluate the associations between the three indices and IFG or T2DM. Restricted cubic spline curves based on the Cox regression model were used to examine the association between baseline indices and incident T2DM.

Results

For the baseline data, logistic analyses demonstrated that the TyG index, TG/HDL-C ratio, and METS-IR had a significantly positive correlation with IFG or T2DM after multivariable adjustment. During a median follow-up of 12.17 years, 157 incident cases of IFG and 97 incident cases of T2DM were noted. The risk of T2DM, but not IFG, was strongly associated with the baseline TyG index in the adjusted model, and participants with the TyG index in the third tertile had a higher risk of developing T2DM (adjusted hazards ratio, 2.84; 95% confidence intervals, 1.26–6.37; p for trend <0.001) than those in the lowest tertile (reference). Moreover, a linear relationship was observed between the TyG index and T2DM incidence. The TG/HDL-C ratio and METS-IR had no significant relationship with the risk of IFG or T2DM.

Conclusion

The TyG index is more useful than the TG/HDL-C ratio and METS-IR in predicting T2DM in the normoglycemic population.

Abbreviations

BMI, body mass index; CI, confidence interval; DBP, diastolic blood pressure; FBG, fasting blood glucose; FPG, fasting plasma glucose; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, insulin-based homeostasis model assessment index; HR, hazards ratio; IFG, impaired fasting glucose; IR, insulin resistance; LDL-C, low-density lipoprotein cholesterol; METS-IR, metabolic score for insulin resistance; OR, odds ratio; SBP, systolic blood pressure; T2DM, type 2 diabetes mellitus; TC, total cholesterol; TG, triglyceride; TG/HDL-C, triglyceride-to-high-density lipoprotein cholesterol; TyG, triglyceride-glucose; WC, waist circumference; WHtR, waist-to-height ratio.

Data Sharing Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Ethics Approval and Informed Consent

The study protocol was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by the Medical Ethics Review Committee of the Ningxia Medical University. All participants consented to participate in the study and provided written informed consent.

Acknowledgments

We thank all the participants and staff included in this cross-sectional cohort study.

Author Contributions

YHZ and YZ conceived and designed research. XXL, YXX, YYD, WLL and QNW contributed to collect the data. XXL and YXX conducted experiments, analyzed data and drafted the manuscript. YHZ and YZ contributed to revise the paper. All authors contributed to data analysis, drafting or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (grant number 81860603, 2019), the Natural Science Foundation of Ningxia Hui Autonomous Region (grant number 2020AAC03167, 2020), the Natural Science Foundation of Ningxia Province (grant number 2021AAC03128, 2021), and the university-level project of Ningxia Medical University (grant number XT2019010, 2019).