Association of METS-IR Index with Type 2 Diabetes: A Cross-sectional Analysis of National Health and Nutrition Examination Survey Data from 2009 to 2018
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Background
With rising global diabetes prevalence, precise early identification and management of diabetes risk are critical research areas. The METS-IR, a novel non-insulin-based tool, is gaining attention for quantifying insulin resistance using multiple metabolic parameters. Despite its potential in predicting diabetes and its precursors, evidence on its specific relationship with diabetes is limited, especially in large-scale population validation and mechanistic exploration.
Objective
This study aims to analyze the association between METS-IR and type 2 diabetes (T2DM) in American adults.
Methods
We conducted a cross-sectional analysis of NHANES data from 2009 to 2018. Participants aged 20 years and above were included, excluding individuals with missing data on BMI, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDL-C), glycated hemoglobin (HbA1c) and diabetes status. Logistic regression analysis, subgroup analysis, and restricted cubic spline analysis were used to assess the association between METS-IR and T2DM, controlling for potential confounding factors.
Results
After adjusting for age, gender, race, education level, smoking status, drinking habits, depression, physical activity, hypertension, and hyperlipidemia, we found a positive association between METS-IR and the risk of T2DM. Specifically, each unit increase in METS-IR was associated with a 7% increase in the risk of T2DM (OR=1.07, 95% CI: 1.06, 1.08). Subgroup analysis showed that the association between METS-IR and T2DM incidence was significantly positive in the highest quartile group, particularly among Mexican Americans over 40 years old and those diagnosed with depression, hypertension, or hyperlipidemia.
Conclusion
Our study revealed a significant positive association between METS-IR and the prevalence of T2DM, indicating that this relationship persists even after controlling for various confounding factors. Therefore, monitoring METS-IR may provide a valuable tool for the early identification of individuals at risk of glucose metabolism disorders. Further research should focus on the applicability of METS-IR in different populations and its potential impact on clinical practice.
