An exploration of the relationship between skeletal muscle mass and glucose intolerance in healthy young adults

University essay from Högskolan i Halmstad/Akademin för företagande, innovation och hållbarhet

Abstract: Background Type 2 diabetes mellitus (T2DM) is a globally prevalent disease anticipated to double from 500 million diagnosed cases in 2021 to more than one billion by 2050. The investigation of the potentially protective effects of skeletal muscle mass on glucose intolerance may lead to the development of more precise screening protocols. Purpose This thesis aimed to address the lack of clear consensus in existing literature by exploring the relationship between skeletal muscle mass and glucose intolerance. Methods Fifteen healthy young adults were recruited to partake in a prospective correlational study. The participants underwent anthropometric measurements and an oral glucose tolerance test (OGTT). Anthropometric data was collected using an bioelectrical impedance analysis (BIA) scale. Blood glucose levels were measured using capillary sampling before and after ingestion of a 75 g/200 mL glucose solution. Statistical analysis included Spearman’s rank correlation test and Pearson’s correlation coefficient test. Results All associations between skeletal muscle mass and glucose intolerance were of moderate strength. Skeletal muscle mass (SMM) correlated significantly with glucose concentrations two hours (2hPG) following ingestion of the glucose solution and an adjusted measure of SMM was significantly associated with glucose area under the curve (AUC). Statistical significance was also found between Sex and incremental glucose area under the curve (iAUC). Conclusion This thesis suggests an inverse relationship between skeletal muscle mass and glucose intolerance in a group of healthy young adults. The results imply the potential usefulness of incorporating muscle mass when determining the glucose load during an OGTT, especially in preventive contexts. Nevertheless, further research with larger samples is crucial to establish precise cutoff levels for clinical applications.

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