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Background <p>Since 1980, the number of people with diabetes has doubled globally, a figure expected to reach 783&#xa0;million by 2045. The Muscle Quality Index (MQI) is a comprehensive indicator of muscle health, which integrates muscle mass, strength, and functional performance. However, its relationship with diabetes remains unexplored in American adults. This study investigates the relationship between MQI, and type 2 diabetes based on the NHANES database.</p> Methods <p>We analyzed 4088 adults aged 20–60 years from NHANES 2011–2014. Three MQI parameters were calculated: MQI<sub>arm</sub>, MQI<sub>app</sub>, and MQI<sub>total</sub>. Statistical analyses included logistic regression, subgroup analysis, RCS, mediation analysis, and advanced machine learning methods.</p> Results <p>Participants with diabetes demonstrated significantly lower MQI values compared to non-diabetic participants, MQI<sub>arm</sub> (11.04 ± 2.07 vs. 12.85 ± 2.39, <i>p</i> &lt; 0.001), MQI<sub>app</sub> (1.53 ± 0.30 vs. 1.77 ± 0.32, <i>p</i> &lt; 0.001), and MQI<sub>total</sub> (2.97 ± 0.56 vs. 3.44 ± 0.60, <i>p</i> &lt; 0.001). Logistic regression and RCS analysis confirmed MQI is inversely associated with diabetes with a linear relationship (p for overall &lt; 0.001, p for nonlinear = 0.458), with consistent associations across demographic and clinical subgroups. Mediation analysis identified that HDL and BMI serve as mediators between MQI and diabetes. Machine learning and Boruta analysis emphasize MQI parameters as key predictors for diabetes risk. ROC curve indicates that MQI has superior AUC compared to traditional parameters including muscle mass and BMI.</p> Conclusion <p>MQI demonstrates a significant inverse association with diabetes through direct and HDL/BMI-mediated indirect pathways. These findings reveal that MQI is a promising, non-invasive indicator for diabetes risk assessment and highlight the significance of improving muscle quality in diabetes prevention strategies.</p>

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Protector role of muscle quality against diabetes in non-elderly U.S. adults

  • 期刊论文

  • 发表日期：

    2025年12月23日

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  • Xingyu Yao,
  • Kaiwen Xiao,
  • Hein Ko Oo

摘要

Background

Since 1980, the number of people with diabetes has doubled globally, a figure expected to reach 783 million by 2045. The Muscle Quality Index (MQI) is a comprehensive indicator of muscle health, which integrates muscle mass, strength, and functional performance. However, its relationship with diabetes remains unexplored in American adults. This study investigates the relationship between MQI, and type 2 diabetes based on the NHANES database.

Methods

We analyzed 4088 adults aged 20–60 years from NHANES 2011–2014. Three MQI parameters were calculated: MQIarm, MQIapp, and MQItotal. Statistical analyses included logistic regression, subgroup analysis, RCS, mediation analysis, and advanced machine learning methods.

Results

Participants with diabetes demonstrated significantly lower MQI values compared to non-diabetic participants, MQIarm (11.04 ± 2.07 vs. 12.85 ± 2.39, p < 0.001), MQIapp (1.53 ± 0.30 vs. 1.77 ± 0.32, p < 0.001), and MQItotal (2.97 ± 0.56 vs. 3.44 ± 0.60, p < 0.001). Logistic regression and RCS analysis confirmed MQI is inversely associated with diabetes with a linear relationship (p for overall < 0.001, p for nonlinear = 0.458), with consistent associations across demographic and clinical subgroups. Mediation analysis identified that HDL and BMI serve as mediators between MQI and diabetes. Machine learning and Boruta analysis emphasize MQI parameters as key predictors for diabetes risk. ROC curve indicates that MQI has superior AUC compared to traditional parameters including muscle mass and BMI.

Conclusion

MQI demonstrates a significant inverse association with diabetes through direct and HDL/BMI-mediated indirect pathways. These findings reveal that MQI is a promising, non-invasive indicator for diabetes risk assessment and highlight the significance of improving muscle quality in diabetes prevention strategies.