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.

A total of 90 elderly patients with diabetes mellitus were included in the study, with a mean age of 68.7 ± 5.8 years. The largest proportion belonged to the 60–64-year age group (30.0%), followed by 65–69 years (27.8%). Males constituted 52.2% of the study population, while 60.0% were from urban areas. Most participants were married (67.8%). The mean BMI was 23.6 ± 3.8 kg/m², with 32.2% being overweight (BMI ≥25 kg/m²) and 10.0% underweight. (Table 1).

Table 1. Baseline Characteristics of the Study Participants (N = 90)

The mean duration of diabetes was 9.8 ± 4.6 years, with 40.0% of participants having diabetes for more than 10 years. The mean HbA1c was 8.2 ± 1.4%, and nearly one-third (31.1%) had poor glycemic control (HbA1c ≥9%). Oral hypoglycemic agents were the most common treatment (53.3%), while hypertension (64.4%) and dyslipidemia (51.1%) were the predominant comorbidities. Chronic kidney disease was present in 16.7% of participants, whereas 26.7% and 22.2% reported smoking and alcohol consumption, respectively (Table 2).

Table 2. Clinical and Diabetes-related Characteristics (N = 90)

Assessment of nutritional and functional status showed that 43.3% of participants were at risk of malnutrition and 17.8% were malnourished according to the MNA-SF. Low handgrip strength and reduced muscle mass were observed in 41.1% and 37.8% of participants, respectively. Slow gait speed (<0.8 m/s) was identified in 33.3%, while 36.7% had a SARC-F score suggestive of sarcopenia risk (Table 3).

Table 3. Nutritional, Functional and Sarcopenia Assessment (N = 90)

Based on the EWGSOP2 criteria, sarcopenia was diagnosed in 31 of the 90 participants, yielding a prevalence of 34.4%. Among individuals with sarcopenia, confirmed sarcopenia was the most common category (41.9%), followed by probable sarcopenia (38.7%), whereas severe sarcopenia accounted for 19.4% of cases (Table 4).

Table 4. Prevalence and Severity of Sarcopenia (N = 90)

Participants with sarcopenia were significantly older and more likely to have diabetes duration exceeding 10 years, poor glycemic control (HbA1c ≥9%), lower BMI, chronic kidney disease, malnutrition or risk of malnutrition, and reduced gait speed compared with those without sarcopenia (p<0.05). Although hypertension and male gender were more frequent among participants with sarcopenia, these associations did not achieve statistical significance (Table 5).

Table 5. Association Between Baseline Variables and Sarcopenia

Multivariable logistic regression demonstrated that increasing age, diabetes duration greater than 10 years, HbA1c ≥9%, BMI <23 kg/m², chronic kidney disease, malnutrition or risk of malnutrition, and low gait speed were independent predictors of sarcopenia. Among these variables, low gait speed (AOR=6.47) and malnutrition/risk of malnutrition (AOR=5.18) showed the strongest independent associations with sarcopenia (Table 6).

Table 6. Multivariable Logistic Regression Analysis for Predictors of Sarcopenia

The present study evaluated the burden of sarcopenia among elderly patients with type 2 diabetes mellitus and demonstrated a prevalence of 34.4% based on the EWGSOP2 criteria. This finding indicates that nearly one-third of elderly diabetic individuals are affected by sarcopenia, highlighting its importance as a geriatric complication of diabetes. The observed prevalence is comparable to previous Indian studies, which reported sarcopenia prevalence ranging from 22% to 31% among older adults with diabetes [12]. Likewise, a systematic review and meta-analysis by Veronese et al. reported that diabetes significantly increased the likelihood of sarcopenia compared with non-diabetic individuals (OR 1.64), emphasizing the close association between these two conditions [13]. Similarly, a recent meta-analysis by Feng et al. reported an overall prevalence of approximately 18–23%, with higher rates observed in hospital-based elderly diabetic populations and when contemporary diagnostic criteria were applied [14]. Increasing age emerged as an independent predictor of sarcopenia in the present study, with patients having sarcopenia being significantly older than those without the condition. In addition, diabetes duration exceeding 10 years and poor glycemic control (HbA1c ≥9%) were independently associated with sarcopenia. These observations are consistent with previous reports suggesting that prolonged exposure to hyperglycemia, insulin resistance, oxidative stress, chronic inflammation, and accumulation of advanced glycation end-products accelerate skeletal muscle loss and impair muscle regeneration [15]. Similar associations between older age, longer diabetes duration, and elevated HbA1c with sarcopenia have been demonstrated in several observational studies and pooled meta-analyses, reinforcing the role of sustained metabolic dysregulation in the development of frailty among elderly diabetic patients [9,14]. The present study also demonstrated that lower BMI, chronic kidney disease, malnutrition or risk of malnutrition, and reduced gait speed were significantly associated with sarcopenia. Multivariable analysis further identified low gait speed and malnutrition/risk of malnutrition as the strongest independent predictors. These findings agree with the EWGSOP2 consensus, which recognizes impaired muscle strength and physical performance as essential components of sarcopenia diagnosis [12]. Furthermore, recent studies have consistently shown that poor nutritional status and reduced physical performance substantially increase the risk of sarcopenia, while diabetic nephropathy and other chronic complications further aggravate muscle wasting through inflammation, protein-energy imbalance, and reduced physical activity [9,14]. These findings emphasize that sarcopenia is a multifactorial condition influenced by metabolic, nutritional, and functional factors. The findings of the present study have important clinical implications. Since many of the identified risk factors, including poor glycemic control, malnutrition, and physical inactivity, are potentially modifiable, routine screening for sarcopenia among elderly individuals with diabetes should become an integral component of comprehensive diabetes care. Early identification using simple tools such as the SARC-F questionnaire, handgrip strength measurement, gait speed assessment, and nutritional evaluation may facilitate timely multidisciplinary interventions involving nutritional optimization, resistance exercise, and individualized diabetes management. Such strategies may help preserve muscle function, reduce frailty, improve quality of life, and minimize disability and hospitalization among elderly diabetic patients.

Sarcopenia is a common yet frequently underrecognized complication among elderly patients with type 2 diabetes mellitus, affecting approximately one-third of the study population. Increasing age, longer duration of diabetes, poor glycemic control, lower BMI, chronic kidney disease, malnutrition, and reduced gait speed were identified as significant predictors of sarcopenia. Routine screening using simple clinical tools, combined with nutritional assessment and functional evaluation, may facilitate early diagnosis and timely intervention. Integrating sarcopenia assessment into routine diabetes care could help reduce frailty, preserve physical function, improve quality of life, and minimize disability among older adults with diabetes.

Acknowledgement: None

Funding: None

Conflict of Interest: None

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