The global population is aging rapidly, leading to a substantial increase in the prevalence of chronic non-communicable diseases, particularly type 2 diabetes mellitus (T2DM) [1]. Older adults with diabetes are at a significantly higher risk of functional decline, disability, hospitalization, and mortality than their non-diabetic counterparts [2]. In addition to the metabolic complications traditionally associated with diabetes, age-related loss of skeletal muscle mass and function has emerged as an important determinant of adverse health outcomes in this population [3]. Sarcopenia, characterized by progressive decline in muscle strength, muscle mass, and physical performance, has therefore become a major public health concern among elderly individuals with diabetes [4].

 

Diabetes accelerates the development of sarcopenia through multiple pathophysiological mechanisms, including insulin resistance, chronic low-grade inflammation, oxidative stress, mitochondrial dysfunction, impaired protein synthesis, and diabetic neuropathy [5]. Poor glycemic control further exacerbates muscle catabolism, resulting in reduced muscle quality and strength [6]. The coexistence of sarcopenia and diabetes contributes to a vicious cycle of reduced mobility, frailty, falls, fractures, impaired quality of life, and increased healthcare utilization [7]. Consequently, sarcopenia is increasingly recognized as a significant diabetes-related complication requiring timely identification and intervention [8].

 

Recent consensus guidelines, particularly those proposed by the European Working Group on Sarcopenia in Older People (EWGSOP2), emphasize the importance of evaluating muscle strength, muscle quantity, and physical performance for the diagnosis of sarcopenia [9]. Screening tools such as the SARC-F questionnaire and nutritional assessments including the Mini Nutritional Assessment–Short Form (MNA-SF) facilitate early identification of high-risk individuals in routine clinical practice [10]. Although several international studies have demonstrated a higher prevalence of sarcopenia among older adults with diabetes, considerable variation exists across different populations due to differences in ethnicity, nutritional status, lifestyle, comorbidities, and healthcare access [11]. Furthermore, evidence from the Indian elderly diabetic population remains relatively limited, highlighting the need for region-specific data to better understand the burden and determinants of sarcopenia.

 

The present study aimed to determine the prevalence of sarcopenia among elderly patients with type 2 diabetes mellitus and to evaluate the demographic, clinical, nutritional, and functional factors associated with sarcopenia in this population.

This hospital-based cross-sectional observational study was conducted in the Department of General Medicine over a period of one year, from October 2024 to October 2025, after obtaining approval from the Institutional Ethics Committee. A total of 90 elderly patients (aged ≥60 years) with diagnosed type 2 diabetes mellitus attending the outpatient and inpatient services during the study period were enrolled using consecutive sampling after obtaining written informed consent. Patients with acute critical illness, advanced malignancy, severe neurological disorders affecting mobility, recent major trauma or surgery, and those unwilling to participate were excluded from the study. Baseline demographic and clinical data, including age, sex, residence, marital status, body mass index (BMI), duration of diabetes, treatment modality, smoking and alcohol history, and associated comorbidities such as hypertension, dyslipidemia, coronary artery disease, and chronic kidney disease, were recorded using a predesigned case record form. Glycemic control was assessed using glycated hemoglobin (HbA1c) values obtained during the study period. Nutritional status was evaluated using the Mini Nutritional Assessment–Short Form (MNA-SF). All participants underwent a comprehensive assessment for sarcopenia in accordance with the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) recommendations. Muscle strength was assessed using handgrip strength measured with a calibrated hand dynamometer, while physical performance was evaluated by gait speed over a standardized walking distance. Muscle mass was assessed using the institution's standard body composition assessment method, and participants were classified as having probable, confirmed, or severe sarcopenia based on EWGSOP2 criteria. The SARC-F questionnaire was also administered as a screening tool to identify individuals at increased risk of sarcopenia. All collected data were entered into Microsoft Excel and analyzed using Statistical Package for the Social Sciences (SPSS) software version 20 (IBM Corp., Armonk, NY, USA). Continuous variables were expressed as mean ± standard deviation, while categorical variables were summarized as frequencies and percentages. Comparisons between participants with and without sarcopenia were performed using the independent Student's t-test for continuous variables and the Chi-square test or Fisher's exact test for categorical variables, as appropriate. Variables showing significant associations on univariate analysis were included in a multivariable logistic regression model to identify independent predictors of sarcopenia. A two-tailed p value of <0.05 was considered statistically significant.