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. 2022 Jan-Feb;19(1):14791641211070281.
doi: 10.1177/14791641211070281.

Function outperforms morphology in the assessment of muscular contribution to insulin sensitivity in premenopausal women

Affiliations

Function outperforms morphology in the assessment of muscular contribution to insulin sensitivity in premenopausal women

Lorena Wanger et al. Diab Vasc Dis Res. 2022 Jan-Feb.

Abstract

Introduction: Skeletal muscle contributes significantly to insulin sensitivity in humans. However, which non-invasive measurement best reflects this contribution remains unknown. Consequently, this paper compares morphologic and functional measurements.

Research methods and design: We conducted a cross-sectional analysis of 144 premenopausal women enrolled in the "Prediction, Prevention, and Sub-classification of Type 2 Diabetes" (PPSDiab) cohort study. For the analysis, we quantified insulin sensitivity by oral glucose tolerance testing and, in a subgroup of 30 women, euglycemic clamp. To assess skeletal muscle, we measured volume by magnetic resonance imaging, intramyocellular lipid content by magnetic resonance spectroscopy, and physical fitness by cardiopulmonary exercise testing.

Results: The mean age of the cohort was 35.7 ± 4.1 years and 94 participants (65%) had a history of gestational diabetes mellitus. Of the morphologic and functional muscle parameters, the maximum workload achieved during cardiopulmonary exercise testing associated most closely with insulin sensitivity (standardized beta = 0.39; p < .001). Peak oxygen uptake also demonstrated significant associations, whereas muscle volume and intramyocellular lipid content displayed none.

Conclusion: Functional measurements provided a better assessment of the muscular contribution to insulin sensitivity than morphologic measurements in premenopausal women. In particular, exercise testing rendered an easy and cost-effective method applicable in clinical settings and other human studies.

Keywords: exercise testing; insulin resistance; magnetic resonance imaging; muscle volume; type 2 diabetes.

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Conflict of interest statement

Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Graphical representation of the most important linear regression models from Tables 2 and 3. The dependent variables are displayed on the y-axes. In addition to the significant independent variables listed in the graphs, the models underlying A. and C. also included time after delivery and age, B. and D. time after delivery, age and height.

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