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    Obesity Indices, Skeletal Muscle Mass, and Physical Activity are Not Independently Associated with Glycemic Control in Patients with Type 2 Diabetes

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    https://www.riss.kr/link?id=A110286010

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    PURPOSES Obesity is a well-established risk factor for type 2 diabetes mellitus (T2DM). However, non-obese T2DM patients may have worse prognoses due to sarcopenia and beta-cell dysfunction, particularly in Asians. This study investigated associations between obesity indices, skeletal muscle mass, physical activity, and glycemic control in Korean T2DM patients.


    METHODS A total of 179 T2DM patients were classified into non-obese (BMI < 25 kg/m²) and obese (BMI ≥ 25 kg/m²) groups. Obesity indicators included BMI, waist circumference, and body fat percentage; their cumulative effect was assessed using a clustering score (0-3). Skeletal muscle index (SMI) was calculated from bioelectrical impedance analysis. Physical activity was assessed using a questionnaire. Glycemic control was evaluated using fasting plasma glucose (FPG) and HbA1c. Group comparisons and multivariable logistic regression were performed to identify independent predictors of poor glycemic control.


    RESULTS The non-obese group had lower body weight and visceral fat but marked skeletal muscle deficit (p < 0.001). Higher SMI tertiles and physical activity guideline adherence were not associated with improvements in glycemic indices. The obesity clustering score showed no dose-response relationship with FPG, HbA1c, or poor glycemic control. In multivariable analyses, BMI-defined obesity, SMI, and physical activity were not independently associated with poor glycemic control in this study.


    CONCLUSIONS In T2DM patients, BMI-defined obesity, skeletal muscle mass, and physical activity alone may be insufficient to explain glycemic control. These findings highlight T2DM’s metabolic heterogeneity and suggest that single anthropometric or lifestyle indicators may inadequately assess glycemic risk. A multidimensional approach incorporating disease duration, treatment factors, and body composition quality may be required.
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    PURPOSES Obesity is a well-established risk factor for type 2 diabetes mellitus (T2DM). However, non-obese T2DM patients may have worse prognoses due to sarcopenia and beta-cell dysfunction, particularly in Asians. This study investigated associations...

    PURPOSES Obesity is a well-established risk factor for type 2 diabetes mellitus (T2DM). However, non-obese T2DM patients may have worse prognoses due to sarcopenia and beta-cell dysfunction, particularly in Asians. This study investigated associations between obesity indices, skeletal muscle mass, physical activity, and glycemic control in Korean T2DM patients.


    METHODS A total of 179 T2DM patients were classified into non-obese (BMI < 25 kg/m²) and obese (BMI ≥ 25 kg/m²) groups. Obesity indicators included BMI, waist circumference, and body fat percentage; their cumulative effect was assessed using a clustering score (0-3). Skeletal muscle index (SMI) was calculated from bioelectrical impedance analysis. Physical activity was assessed using a questionnaire. Glycemic control was evaluated using fasting plasma glucose (FPG) and HbA1c. Group comparisons and multivariable logistic regression were performed to identify independent predictors of poor glycemic control.


    RESULTS The non-obese group had lower body weight and visceral fat but marked skeletal muscle deficit (p < 0.001). Higher SMI tertiles and physical activity guideline adherence were not associated with improvements in glycemic indices. The obesity clustering score showed no dose-response relationship with FPG, HbA1c, or poor glycemic control. In multivariable analyses, BMI-defined obesity, SMI, and physical activity were not independently associated with poor glycemic control in this study.


    CONCLUSIONS In T2DM patients, BMI-defined obesity, skeletal muscle mass, and physical activity alone may be insufficient to explain glycemic control. These findings highlight T2DM’s metabolic heterogeneity and suggest that single anthropometric or lifestyle indicators may inadequately assess glycemic risk. A multidimensional approach incorporating disease duration, treatment factors, and body composition quality may be required.

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