Abstract
Aim
We sought to evaluate the association of the Geriatric Nutritional Risk Index (GNRI), which assesses nutritional status, and sarcopenia among older individuals with type 2 diabetes mellitus.
Methods
We enrolled 292 type 2 diabetes mellitus patients aged 60 years and above in this cross-sectional study. This study took place at Şişli Hamidiye Etfal Training and Research Hospital (Istanbul, Turkey) between April 2024 and December 2024. European Working Group on Sarcopenia in Older People-2 (EWGSOP2) criteria were used to define sarcopenia. The relationship between sarcopenia and GNRI was investigated by logistic regression models.
Results
The average age was 72 years (range: 60–99). Of the 292 patients, 139 were male and 153 were female. Macrovascular complications and microvascular complications, such as neuropathy and nephropathy, were more common in sarcopenic patients. Low GNRI (< 98) was observed to be more in sarcopenic patients (p < 0.001). Multiple logistic regression analysis revealed an association between sarcopenia and neuropathy (p = 0.002) and macrovascular complications (p = 0.038).
Conclusions
Sarcopenia was more common in elderly type 2 diabetic patients with low GNRI. Our study emphasizes the high rate of malnutrition among sarcopenic patients, with a need for regular screening programs and the determination of elderly subjects requiring nutritional support. GNRI may serve as a screening indicator for the detection of malnutrition and sarcopenia in older diabetic individuals who are hospitalized.
Keywords: geriatric nutritional risk index, sarcopenia, type 2 diabetes mellitus
1. Introduction
Sarcopenia and malnutrition are among the most important geriatric syndromes. Malnutrition and sarcopenia are closely linked, and both conditions are present in many patients. The frequency of sarcopenia is increasing in individuals with type 2 diabetes mellitus (T2DM) [1]. The increase in the frequency of sarcopenia is associated with conditions, such as frailty, falls, and mortality [2]. Additionally, a relationship has been found between diabetic complications and sarcopenia [2, 3].
Malnutrition among older individuals with T2DM can be influenced by factors, such as age, comorbidities, changes in appetite, mobility limitations, medications, and economic status. Malnutrition can enhance the risk of sarcopenia in elderly diabetic patients [2]. The most commonly used test for screening malnutrition in the elderly is the Mini Nutritional Assessment (MNA) test. The Geriatric Nutritional Risk Index (GNRI) is a diagnostic index proposed for hospitalized elderly individuals, calculated using serum albumin levels, body weight, and height [4]. Previous studies have shown that low GNRI in patients with hemodialysis and cirrhosis is associated with decreases in muscle mass, muscle strength, and walking ability [5, 6].
The exact cause of sarcopenia in patients with diabetes mellitus has not been fully elucidated. In the pathogenesis, insulin resistance, mitochondrial dysfunction, and inflammation are considered responsible [7].
Our study sought to examine the screening of sarcopenia among older individuals with T2DM and its relationship with age, gender, body mass index (BMI), and the GNRI.
2. Methodology
A total of 292 patients aged 60 years and above with T2DM, who were admitted to the Internal Medicine Department of the University of Health Sciences, were included in the study. The demographic characteristics, data related to T2DM, and complications of the patients were noted.
The MNA test was used to determine the risk of malnutrition. A hand dynamometer was used to measure handgrip strength, and walking speed was measured using the 4-m walking test. The European Working Group on Sarcopenia in Older People-2 (EWGSOP2) criteria were used to diagnose sarcopenia [8]. According to the revised EWGSOP2 (2018) recommendations, patients were grouped into those with possible sarcopenia with low muscle strength and those without sarcopenia with normal muscle strength.
Muscle strength was assessed by measuring the grip strength of the dominant hand using a Saehan dynamometer. Low muscle strength was characterized as less than 27 kg for men and less than 16 kg for women. A calf circumference measurement of < 31 cm was considered an indicator of reduced muscle mass [8]. In the 4-m walking test, a walking speed of less than 0.8 m/s was defined as slow gait.
Each patient's BMI was determined by dividing their weight in kilograms by their height in meters squared (weight/height2).
The following equation was used to calculate GNRI: 14.89 × serum albumin (g/dL) + 41.7 × (body weight/ideal body weight). The Lorentz equations were used to get the formula's optimal body weight [9]. In this study, the cutoff value of 98 was determined a priori, as GNRI < 98 has been consistently used in elderly and diabetic populations to indicate nutritional risk or malnutrition. Accordingly, patients were divided into two groups: those with a low GNRI score (< 98) and those with a high GNRI score (≥ 98). This stratification enabled the evaluation of clinical and metabolic characteristics according to nutritional risk status, consistent with prior studies in elderly and diabetic populations.
Frailty status was assessed using the Frail score. In the Frail questionnaire (0–5), a score of ≥ 3 indicated frail, a score of one to two indicated prefrail, and a score of 0 indicated nonfrail [10, 11]. The nutritional condition among older individuals was evaluated using the MNA test. In this evaluation, scores below 17 indicated malnutrition, scores between 17 and 23 signified a risk of malnutrition, and scores of 24 or higher reflected adequate nutritional condition [10].
Patients with advanced dementia, immobility, bedridden status, T2DM, liver cirrhosis, those undergoing dialysis, and those with malignancies were not included in the study.
Our study comprised patients 60 years of age and older who were identified as having T2DM according to the American Diabetes Association criteria [12].
The creatinine-based Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation [13] was used to determine eGFR.
The ethics committee at our hospital granted ethical permission for this investigation under protocol number 4354, dated March 26, 2024.
Every participant provided written informed permission. Our study complies with the principles of the Helsinki Declaration.
To assess the distribution of variables, the Kolmogorov–Smirnov test was performed. The mean ± standard deviation was used to describe parametric data, and the median (interquartile range) was used to express nonparametric data. When necessary, Student's t-test, one-way ANOVA, or Kruskal–Wallis test was used to examine group differences. The chi-square test was used to assess categorical variables, which were represented as percentages. Sex-stratified analyses were conducted where feasible; variables that did not meet the minimum expected count of five per cell for the Pearson chi-square test were excluded from sex-specific analyses to preserve statistical validity. Logistic regression analysis (univariate followed by multivariate) was conducted to evaluate the connection between sarcopenia and its components. A p-value below 0.05 was considered statistically significant.
3. Results
According to our research, 22.6% of individuals who have T2DM (n = 65) had sarcopenia. The average duration of diabetes was found to be 15 years, and the average age was 72 years (range: 60–99).
In the sarcopenia group, ischemic heart disease and peripheral artery disease were discovered to be significantly higher among the comorbidities. When comparing the sarcopenia group with the nonsarcopenia group in terms of glucose-lowering treatments (metformin, sulfonylureas, thiazolidinediones, SGLT2 inhibitors, DPP4 inhibitors, insulin, basal + bolus insulin, basal insulin, and premixed insulin), there was no discernible statistically significant change (Table 1).
Table 1.
Comparison of general characteristics and laboratory findings between type 2 diabetic patients with and without sarcopenia.
| Variable | Sarcopenia | Test statistics | ||
|---|---|---|---|---|
| Sarcopenia-n (%) | Sarcopenia + n (%) | χ2 | P | |
| Gender | ||||
| Female | 121 (53.3) | 32 (49.2) | 0.130 | 0.718 |
| Male | 106 (46.7) | 33 (50.8) | ||
| Smoking | 62 (27.3) | 23 (35.4) | 1.595 | 0.207 |
| Alcohol | 14 (6.2) | 7 (10.8) | 1.603 | 0.205 |
| Hypertension | 183 (80.6) | 54 (83.1) | 0.200 | 0.655 |
| Hyperlipidemia | 68 (30.0) | 20 (30.8) | 0.016 | 0.900 |
| Chronic renal disease | 52 (22.9) | 22 (33.8) | 3.196 | 0.074 |
| COPD∗ | 28 (12.3) | 8 (12.3) | 0.001 | 0.995 |
| Cerebrovascular disease | 26 (11.5) | 10 (15.4) | 0.722 | 0.395 |
| Ischemic heart disease | 84 (37.0) | 33 (50.8) | 3.987 | 0.046 |
| Peripheral artery disease | 20 (8.8) | 12 (18.5) | 4.823 | 0.028 |
| Antidiabetic agents | ||||
| Metformin | 151 (66.5) | 36 (55.4) | 2.721 | 0.099 |
| Sulfonylurea | 39 (17.2) | 5 (7.7) | 3.555 | 0.059 |
| Thiazolidinedione | 8 (3.5) | 4 (6.2) | 0.887 | 0.346 |
| SGLT2 inhibitor | 39 (17.2) | 14 (21.5) | 0.646 | 0.422 |
| DPP-4 inhibitors | 93 (41.0) | 24 (36.9) | 0.344 | 0.557 |
| Insulin | 94 (41.4) | 28 (43.1) | 0.058 | 0.810 |
| Basal + bolus insulin | 47 (20.7) | 14 (21.5) | 0.021 | 0.884 |
| Basal insulin | 33 (14.5) | 9 (13.8) | 0.020 | 0.889 |
| Premix insulin | 16 (7.0) | 8 (12.3) | 1.853 | 0.173 |
| Microvascular complication | 146 (64.3) | 44 (67.7) | 0.253 | 0.615 |
| Macrovascular complication | 104 (45.8) | 41 (63.1) | 6.023 | 0.014 |
| Microvascular complication | ||||
| Retinopathy | 78 (34.4) | 30 (46.2) | 3.015 | 0.082 |
| Neuropathy | 97 (42.7) | 37 (56.9) | 4.099 | 0.043 |
| Nephropathy | 78 (34.4) | 32 (49.2) | 4.758 | 0.029 |
| 4-m walk gait speed | ||||
| Slow walking speed, < 0.8 m/s | 28 (12.3) | 58 (89.2) | 143.802 | < 0.001 |
| Usual walking speed, ≥ 0.8 m/s | 199 (87.7) | 7 (10.8) | ||
| Frail Scale | ||||
| Robust | 98 (43.2) | 2 (3.1) | 90.805 | < 0.001 |
| Prefrail | 95 (41.8) | 15 (23.1) | ||
| Frail | 34 (15.0) | 48 (73.8) | ||
| Mini Nutritional Assessment Scales | ||||
| Well-nourished | 137 (60.4) | 6 (9.2) | 93.379 | < 0.001 |
| At risk of malnutrition | 74 (32.6) | 23 (35.4) | ||
| Malnutrition | 16 (7.0) | 36 (55.4) | ||
| Body mass index | ||||
| Normal weight | 33 (14.5) | 21 (32.3) | 10.588 | 0.005 |
| Overweight | 114 (50.2) | 26 (40.0) | ||
| Obesity | 80 (35.2) | 18 (27.7) | ||
| GNRI score | ||||
| < 98 | 101 (44.5) | 46 (70.8) | 13.956 | < 0.001 |
| ≥ 98 | 126 (55.5) | 19 (29.2) | ||
| Mean ± S.D. | Mean ± S.D. | T | P | |
| Height, cm | 164.7 ± 8.0 | 161.2 ± 7.3 | 2.952 | 0.003 |
| Waist circumference, cm | 101.9 ± 17.3 | 90.8 ± 19.2 | 4.378 | 0.001 |
| Median (min., max.) | Median (min., max.) | Z | P | |
| Diabetes duration, yr | 15.0 (1.0; 40.0) | 18.5 (1.0; 50.0) | 2.366 | 0.018 |
| Age, yr | 70.0 (60.0; 90.0) | 75.0 (60.0; 99.0) | 4.617 | < 0.001 |
| Calf circumference, cm | 39.0 (19.0; 55.0) | 25.0 (11.0; 37.0) | −11.953 | < 0.001 |
| Handgrip strength, kg | 25.7 (1.2; 38.5) | 8.1 (1.3; 22.7) | −11.479 | < 0.001 |
| FPG∗∗, mg/dL | 145.0 (48.0; 550.0) | 136.0 (71.0; 647.0) | −0.826 | 0.409 |
| Total cholesterol, mg/dL | 159.0 (60.0; 463.0) | 152.5 (88.0; 290.0) | −1.061 | 0.289 |
| LDL cholesterol, mg/dL | 85.0 (20.0; 251.0) | 78.5 (16.0; 198.0) | −1.346 | 0.178 |
| HbA1C, % | 8.0 (6.5; 19.1) | 7.2 (6.5; 15.8) | −3.034 | 0.002 |
| Urea, mg/dL | 45.0 (11.0; 239.0) | 60.0 (15.0; 195.0) | 2.508 | 0.012 |
| Creatinine, mg/dL | 0.9 (0.5; 3.1) | 1.2 (0.3; 4.7) | 1.874 | 0.061 |
| eGFR∗∗∗, mL/min | 71.9 (20.2; 159.9) | 59.0 (13.5; 229.3) | −2.280 | 0.023 |
| CRP∗∗∗∗, mg/dL | 5.6 (0.0; 13.0) | 6.0 (0.0; 17.0) | 1.778 | 0.075 |
| Albumin, g/L | 38.1 (22.9; 49.6) | 34.7 (2.6; 47.7) | −3.699 | < 0.001 |
| Hemoglobin, g/dL | 11.6 (4.2; 16.7) | 10.0 (6.4; 14.8) | −3.985 | < 0.001 |
Note: The bold values denote statistically significant results (p < 0.05).
∗Chronic obstructive pulmonary disease.
∗∗Fast plasma glucose.
∗∗∗Estimated glomerular filtration rate.
∗∗∗∗C-reactive protein.
The sarcopenia group had a statistically significant increased rate of diabetic macrovascular complications and microvascular complications, such as diabetic neuropathy and diabetic nephropathy. Patients with slow walking speed in the 4-m walking test, those identified as frail in the frailty test, and those found to be malnourished in the MNA were statistically significantly higher in the sarcopenia group. Patients who were overweight or obese, according to BMI, were statistically significantly lower in the sarcopenia group. When the GNRI was categorized as < 98 (low) and ≥ 98 (high), in the sarcopenia group, patients with a low GNRI were found to be statistically substantially more (Table 1).
Height, waist circumference, and calf circumference were all shown to be statistically substantially lower in the sarcopenia group than in the nonsarcopenia group. In terms of diabetes duration and age, the sarcopenia group was statistically considerably higher compared to the nonsarcopenia group. Regarding laboratory values, HbA1c, eGFR, albumin, and hemoglobin levels were considerably lower in the group with sarcopenia than in the group without it. Among the laboratory values, urea and CRP levels were statistically considerably higher in the sarcopenia group (Table 1).
To address potential sex-related differences, subgroup analyses were performed separately for male and female participants. In male patients, those with sarcopenia were significantly older and had lower height, calf circumference, hemoglobin, albumin, and GNRI scores, as well as higher CRP levels compared with nonsarcopenic males (Table 2). The prevalence of cerebrovascular disease, peripheral artery disease, and nephropathy was also higher in the sarcopenic group. Among females, sarcopenic patients were older and had lower calf circumference, handgrip strength, albumin levels, and waist circumference compared with their nonsarcopenic counterparts (Table 3). The frequency of retinopathy and normal BMI was higher in sarcopenic females, and GNRI < 98 was significantly more common in this group.
Table 2.
Comparison of general characteristics and laboratory findings between type 2 diabetic male patients with and without sarcopenia.
| Variable | Sarcopenia | Test statistics | ||
|---|---|---|---|---|
| Sarcopenia-n (%) | Sarcopenia + n (%) | χ2 | P | |
| Smoking | 50 (47.2) | 16 (50.0) | 0.079 | 0.779 |
| Alcohol | 11 (10.4) | 6 (18.8) | 1.595 | 0.207 |
| Hypertension | 81 (76.4) | 23 (71.9) | 0.273 | 0.601 |
| Hyperlipidemia | 23 (21.7) | 9 (28.1) | 0.570 | 0.450 |
| Chronic renal disease | 29 (27.4) | 13 (40.6) | 2.043 | 0.153 |
| COPD∗ | 19 (17.9) | 5 (15.6) | 0.090 | 0.764 |
| Cerebrovascular disease | 8 (7.5) | 7 (21.9) | 5.208 | 0.022 |
| Ischemic heart disease | 47 (44.3) | 18 (56.3) | 1.399 | 0.237 |
| Peripheral artery disease | 14 (13.2) | 9 (28.1) | 3.938 | 0.047 |
| Antidiabetic agents | ||||
| Metformin | 70 (66.0) | 16 (50.0) | 2.692 | 0.101 |
| SGLT2 inhibitor | 21 (19.8) | 8 (25.0) | 0.399 | 0.528 |
| DPP-4 inhibitors | 43 (40.6) | 15 (46.9) | 0.402 | 0.526 |
| Insulin | 45 (42.5) | 11 (34.4) | 0.665 | 0.415 |
| Basal + bolus insulin | 24 (22.6) | 5 (15.6) | 0.729 | 0.393 |
| Basal insulin | 14 (13.2) | 5 (15.6) | 0.121 | 0.728 |
| Microvascular complication | 67 (63.2) | 20 (62.5) | 0.005 | 0.942 |
| Macrovascular complication | 55 (51.9) | 22 (68.8) | 2.834 | 0.092 |
| Microvascular complication | ||||
| Retinopathy | 39 (36.8) | 13 (40.6) | 0.154 | 0.695 |
| Neuropathy | 42 (39.6) | 17 (53.1) | 1.831 | 0.176 |
| Nephropathy | 36 (34.0) | 18 (56.3) | 5.126 | 0.024 |
| Normal weight | 15 (14.2) | 8 (25.0) | 2.108 | 0.349 |
| Overweight | 51 (48.1) | 13 (40.6) | ||
| Obesity | 40 (37.7) | 11 (34.4) | ||
| GNRI score | ||||
| < 98 | 48 (45.3) | 21 (65.6) | 4.068 | 0.044 |
| ≥ 98 | 58 (54.7) | 11 (34.4) | ||
| Mean ± S.D. | Mean ± S.D. | T | P | |
| Height, cm | 164.0 ± 8.3 | 159.3 ± 6.6 | 2.648 | 0.009 |
| Calf circumference, cm | 39.1 ± 5.3 | 24.7 ± 4.4 | 13.424 | < 0.001 |
| Albumin | 38.0 ± 5.1 | 35.4 ± 4.8 | 2.063 | 0.041 |
| Hemoglobin | 11.6 ± 2.1 | 10.1 ± 1.6 | 3.716 | < 0.001 |
| Median (min., max.) | Median (min., max.) | Z | P | |
| Diabetes duration, yr | 15.0 (1.0; 40.0) | 22.0 (1.0; 35.0) | 1.775 | 0.076 |
| Age, yr | 70.0 (60.0; 90.0) | 76.0 (62.0; 99.0) | 3.801 | < 0.001 |
| Waist circumference, cm | 102.5 (68.0; 139.0) | 98 (59.0; 130.0) | −1.678 | 0.093 |
| Handgrip strength, kg | 25.5 (1.2; 37.0) | 8.5 (1.3; 22.7) | −7.676 | < 0.001 |
| FPG∗∗, mg/dL | 149.0 (65.0; 550.0) | 115.0 (78.0; 283.0) | −2.056 | 0.040 |
| Total cholesterol, mg/dL | 169.0 (73.0; 463.0) | 171.0 (88.0; 272.0) | −1.367 | 0.171 |
| LDL cholesterol, mg/dL | 96.0 (28.0; 251.0) | 76.0 (20.0; 144.0) | −1.887 | 0.059 |
| HbA1C, % | 8.1 (6.5; 19.1) | 6.9 (6.5; 11.4) | −3.830 | < 0.001 |
| Urea, mg/dL | 48.0 (16.0; 208.0) | 61.0 (15.0; 169.0) | 1.430 | 0.153 |
| Creatinine, mg/dL | 1.0 (0.5; 3.0) | 1.1 (0.4; 4.7) | 1.350 | 0.177 |
| eGFR∗∗∗, mL/min | 68.4 (22.2; 131.9) | 58.3 (13.5; 209.2) | −1.816 | 0.069 |
| CRP∗∗∗∗, mg/dL | 5.0 (0.0; 12.1) | 7.0 (0.0; 17.0) | 3.053 | 0.002 |
Note: The bold values denote statistically significant results (p < 0.05).
∗Chronic obstructive pulmonary disease.
∗∗Fast plasma glucose.
∗∗∗Estimated glomerular filtration rate.
∗∗∗∗C-reactive protein.
Table 3.
Comparison of general characteristics and laboratory findings between type 2 diabetic female patients with and without sarcopenia.
| Variable | Sarcopenia | Test statistics | ||
|---|---|---|---|---|
| Sarcopenia-n (%) | Sarcopenia + n (%) | χ 2 | P | |
| Smoking | 12 (9.9) | 7 (21.2) | 3.058 | 0.080 |
| Hyperlipidemia | 45 (37.2) | 11 (33.3) | 0.167 | 0.683 |
| Chronic renal disease | 23 (19.0) | 9 (27.3) | 1.076 | 0.300 |
| Ischemic heart disease | 37 (30.6) | 15 (45.5) | 2.566 | 0.109 |
| Antidiabetic agents | ||||
| Metformin | 81 (66.9) | 20 (60.6) | 0.461 | 0.497 |
| SGLT2 inhibitor | 18 (14.9) | 6 (18.2) | 0.215 | 0.643 |
| DPP-4 inhibitors | 50 (41.3) | 9 (27.3) | 2.166 | 0.141 |
| Insulin | 49 (40.5) | 17 (51.5) | 1.286 | 0.257 |
| Basal + bolus insulin | 23 (19.0) | 9 (27.3) | 1.076 | 0.300 |
| Premix insulin | 8 (6.6) | 6 (18.2) | 4.200 | 0.040 |
| Microvascular complication | 79 (65.3) | 24 (72.7) | 0.648 | 0.421 |
| Macrovascular complication | 49 (40.5) | 19 (57.6) | 3.067 | 0.080 |
| Microvascular complication | ||||
| Retinopathy | 39 (32.2) | 17 (51.5) | 4.167 | 0.041 |
| Neuropathy | 55 (45.5) | 20 (60.6) | 2.383 | 0.123 |
| Nephropathy | 42 (34.7) | 14 (42.4) | 0.667 | 0.414 |
| Body mass index | ||||
| Normal weight | 18 (14.9) | 13 (39.4) | 9.779 | 0.008 |
| Overweight | 63 (52.1) | 13 (39.4) | ||
| Obesity | 40 (33.0) | 7 (21.2) | ||
| GNRI score | ||||
| < 98 | 53 (43.8) | 25 (75.8) | 10.593 | 0.001 |
| ≥ 98 | 68 (56.2) | 8 (24.2) | ||
| Mean ± S.D. | Mean ± S.D. | T | P | |
| Height, cm | 165.3 ± 7.8 | 163.0 ± 7.5 | 1.483 | 0.140 |
| Waist circumference, cm | 102.3 ± 17.6 | 87.2 ± 16.9 | 4.284 | < 0.001 |
| Hemoglobin | 11.4 ± 2.4 | 10.5 ± 2.2 | 2.025 | 0.045 |
| Median (min., max.) | Median (min., max.) | Z | P | |
| Diabetes duration, yr | 14.0 (1.0; 40.0) | 16.0 (1.0; 50.0) | 1.527 | 0.127 |
| Age, yr | 70.0 (60.0; 89.0) | 75.0 (62.0; 96.0) | 2.733 | 0.006 |
| Calf circumference, cm | 39.0 (19.0; 55.0) | 25.0 (11.0; 30.0) | −8.670 | < 0.001 |
| Handgrip strength, kg | 26.8 (3.9; 38.5) | 7.0 (2.0; 15.6) | −8.492 | < 0.001 |
| FPG∗∗, mg/dL | 139.0 (48.0; 394.0) | 144.0 (71.0; 647.0) | 0.828 | 0.408 |
| Total cholesterol, mg/dL | 152.0 (60.0; 317.0) | 146.0 (89.0; 290.0) | −0.161 | 0.872 |
| LDL cholesterol, mg/dL | 77.0 (20.0; 215.0) | 81.0 (16.0; 198.0) | −0.018 | 0.986 |
| HbA1C, % | 7.8 (6.5; 17.2) | 7.4 (6.5; 15.8) | −0.609 | 0.542 |
| Urea, mg/dL | 40.0 (11.0; 239.0) | 59.0 (17.0; 195.0) | 2.030 | 0.042 |
| Creatinine, mg/dL | 0.9 (0.5; 3.1) | 1.2 (0.3; 3.2) | 1.398 | 0.162 |
| eGFR∗∗∗, mL/min | 76.2 (20.2; 159.9) | 59.1 (20.9; 229.3) | −1.429 | 0.153 |
| CRP∗∗∗∗, mg/dL | 6.0 (0.0; 13.0) | 6.0 (0.0; 12.1) | −0.179 | 0.858 |
| Albumin | 37.6 (23.6; 49.6) | 34.6 (2.6; 47.7) | −2.977 | 0.003 |
Note: The bold values denote statistically significant results (p < 0.05).
∗∗Fast plasma glucose.
∗∗∗Estimated glomerular filtration rate.
∗∗∗∗C-reactive protein.
The variables that were significantly correlated with sarcopenia were subjected to multiple logistic regression analysis, as shown in Table 4. First, the Hosmer–Lemeshow test, which is used to assess goodness of fit, showed a χ2 = 2.222 (p = 0.973 > 0.05), indicating that the model is a good fit. The Nagelkerke R2 value was 0.685, indicating that 68.5% of the variation in sarcopenia status is explained by the variables listed in Table 4.
Table 4.
Results of the multiple logistic regression model for variables that related to sarcopenia.
| Variable | Wald | P | Exp (β) | 95% C.I odds ratio | |||
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| Constant | −5.215 | 1.077 | 23.442 | < 0.001 | 0.005 | ||
| Ischemic heart disease | −0.684 | 0.646 | 1.122 | 0.289 | 0.504 | 0.142 | 1.789 |
| Peripheral artery disease | −0.879 | 0.714 | 1.517 | 0.218 | 0.415 | 0.102 | 1.682 |
| Macrovascular complication | 1.461 | 0.704 | 4.307 | 0.038 | 4.309 | 1.085 | 17.119 |
| Neuropathy | 1.991 | 0.651 | 9.365 | 0.002 | 7.326 | 2.046 | 26.322 |
| Nephropathy | −0.025 | 0.568 | 0.002 | 0.965 | 0.975 | 0.321 | 2.966 |
| Slow walking speed | 3.846 | 0.712 | 29.164 | < 0.001 | 46.818 | 11.592 | 189.081 |
| Prefrail | 1.392 | 0.947 | 2.162 | 0.141 | 4.024 | 0.629 | 25.749 |
| Frail | 1.502 | 1.028 | 2.135 | 0.144 | 4.491 | 0.599 | 33.672 |
| At risk of malnutrition | −0.374 | 0.799 | 0.219 | 0.640 | 0.688 | 0.144 | 3.296 |
| Malnutrition | 1.156 | 0.957 | 1.459 | 0.227 | 3.176 | 0.487 | 20.713 |
| Overweight | −0.964 | 0.589 | 2.679 | 0.102 | 0.382 | 0.120 | 1.210 |
| Obesity | −0.506 | 0.654 | 0.597 | 0.440 | 0.603 | 0.167 | 2.175 |
| GNRI score ≥ 98 | −0.563 | 0.512 | 1.209 | 0.272 | 0.570 | 0.209 | 1.553 |
Note: −2 Log likelihood = 136.400.
As a result of the multiple logistic regression analysis, the variables listed in Table 4 were obtained. It was found that the likelihood of having sarcopenia was 4.309 times higher in individuals with macrovascular complications compared to those without. The likelihood of having sarcopenia was 7.326 times higher in individuals with neuropathy, a microvascular complication, compared to those without neuropathy. Additionally, individuals with a slow walking speed in the 4-m walking test were found to be 46.818 times more likely to have sarcopenia in contrast to those with normal walking speed (Table 4).
When comparing patients with a GNRI < 98 (low) and ≥ 98 (high) in terms of comorbidities, a higher prevalence of hypertension was found in the low GNRI group. In the high GNRI group, the prevalence of microvascular complications and neuropathy among the microvascular complications was statistically significantly higher. In the low GNRI group, a statistically significant higher prevalence of frail patients based on frailty scores and malnourished patients based on the MNA was found. When evaluated based on BMI, overweight and obese patients were discovered to be statistically considerably lower in the low GNRI group (Table 5).
Table 5.
Comparison of general characteristics and laboratory findings in GNRI subgroups of patients with type 2 diabetes.
| Variable | GNRI score | Test statistics | ||
|---|---|---|---|---|
| < 98n (%) | ≥ 98n (%) | T | P | |
| Gender | ||||
| Female | 78 (53.1) | 76 (52.4) | 0.012 | 0.912 |
| Male | 69 (46.9) | 69 (47.6) | ||
| Smoking | 42 (28.6) | 43 (29.7) | 0.042 | 0.838 |
| Alcohol | 11 (7.5) | 10 (6.9) | 0.038 | 0.846 |
| Hypertension | 127 (86.4) | 110 (75.9) | 5.297 | 0.021 |
| Hyperlipidemia | 43 (29.3) | 45 (31.0) | 0.110 | 0.740 |
| Chronic renal disease | 39 (26.5) | 35 (24.1) | 0.221 | 0.638 |
| COPD∗ | 20 (13.6) | 16 (11.0) | 0.446 | 0.504 |
| Cerebrovascular disease | 15 (10.2) | 21 (14.5) | 1.236 | 0.266 |
| Ischemic heart disease | 66 (44.9) | 51 (35.2) | 2.875 | 0.090 |
| Peripheral artery disease | 13 (8.8) | 19 (13.1) | 1.358 | 0.244 |
| Antidiabetic agents | ||||
| Metformin | 89 (60.5) | 98 (67.6) | 1.572 | 0.210 |
| Sulfonylurea | 21 (14.3) | 23 (15.9) | 0.142 | 0.707 |
| SGLT2 inhibitors | 21 (14.3) | 32 (22.1) | 2.977 | 0.084 |
| DPP-4 inhibitors | 56 (38.1) | 61 (42.1) | 0.480 | 0.488 |
| Insulin | 64 (43.5) | 58 (40.0) | 0.376 | 0.540 |
| Basal + bolus insulin | 33 (22.4) | 28 (19.3) | 0.435 | 0.509 |
| Basal insulin | 23 (15.6) | 19 (13.1) | 0.383 | 0.536 |
| Premix insulin | 12 (8.2) | 12 (8.3) | 0.001 | 0.972 |
| Microvascular complication | 79 (53.7) | 111 (67.7) | 16.710 | < 0.001 |
| Macrovascular complication | 71 (48.3) | 74 (51.0) | 0.218 | 0.640 |
| Microvascular complication | ||||
| Retinopathy | 47 (32.0) | 61 (42.1) | 3.193 | 0.074 |
| Neuropathy | 56 (38.1) | 78 (53.8) | 7.244 | 0.007 |
| Nephropathy | 54 (36.7) | 56 (38.6) | 0.111 | 0.739 |
| 4-m walk gait speed | ||||
| Slow walking speed,< 0.8 m/s | 60 (40.8) | 26 (17.9) | 18.400 | < 0.001 |
| Usual walking speed, ≥ 0.8 m/s | 87 (59.2) | 119 (82.1) | ||
| Frail Scale | ||||
| Robust | 39 (26.5) | 61 (42.1) | 21.941 | < 0.001 |
| Prefrail | 49 (33.3) | 61 (42.1) | ||
| Frail | 59 (40.2) | 23 (15.8) | ||
| Mini Nutritional Assessment Scales | ||||
| Well-nourished | 53 (36.1) | 90 (62.1) | 27.704 | < 0.001 |
| At risk of malnutrition | 53 (36.1) | 44 (30.3) | ||
| Malnutrition | 41 (27.8) | 11 (7.6) | ||
| Body mass index | ||||
| Normal weight | 37 (25.2) | 17 (11.7) | 10.035 | 0.007 |
| Overweight | 69 (46.9) | 71 (49.0) | ||
| Obesity | 41 (27.9) | 57 (39.3) | ||
| Mean ± S.D | Mean ± S.D. | T | P | |
| Height, cm | 164.7 ± 7.5 | 163.1 ± 8.4 | 1.425 | 0.155 |
| Waist circumference, cm | 95.3 ± 18.4 | 103.5 ± 17.4 | −3.599 | < 0.001 |
| Hemoglobin, g/dL | 10.5 ± 2.1 | 12.0 ± 2.1 | −6.201 | < 0.001 |
| Median (min., max.) | Median (min., max.) | Z | P | |
| Diabetes duration, yr | 12.0 (1.0; 50.0) | 16.0 (1.0; 40.0) | 2.119 | 0.034 |
| Age, yr | 72.0 (60.0; 94.0) | 70.0 (60.0; 99.0) | −2.688 | 0.007 |
| Calf circumference, cm | 35.0 (11.0; 54.0) | 39.0 (16.0; 55.0) | 4.908 | < 0.001 |
| Handgrip strength, kg | 21.3 (1.2; 38.5) | 24.1 (2.0; 36.5) | 1.490 | 0.136 |
| FPG∗∗, mg/dL | 145.0 (48.0; 647.0) | 141.0 (66.0; 476.0) | 0.613 | 0.540 |
| Total cholesterol, mg/dL | 140.5 (60.0; 290.0) | 174.0 (84.0; 463.0) | 4.409 | < 0.001 |
| LDL cholesterol, mg/dL | 75.0 (16.0; 198.0) | 94.0 (28.0; 251.0) | 3.250 | 0.001 |
| HbA1C, % | 7.6 (6.5; 19.1) | 7.8 (6.5; 17.0) | 1.200 | 0.230 |
| Urea, mg/dL | 55.0 (11.0; 239.0) | 40.0 (16.0; 137.0) | −3.187 | 0.001 |
| Creatinine, mg/dL | 1.1 (0.3; 4.7) | 0.9 (0.5; 2.4) | −2.647 | 0.008 |
| eGFR∗∗∗, mL/min | 62.3 (13.5; 229.3) | 76.9 (20.6; 133.3) | 2.121 | 0.034 |
| CRP∗∗∗∗, mg/dL | 6.0 (1.0; 17.0) | 5.0 (0.0; 13.0) | −3.488 | < 0.001 |
| Albumin, g/L | 33.3 (2.6; 41.3) | 41.2 (37.5; 49.6) | 14.647 | < 0.001 |
Note: The bold values indicate statistically significant results (p < 0.05) in the comparison between the GNRI subgroups.
∗Chronic obstructive pulmonary disease.
∗∗Fast plasma glucose.
∗∗∗Estimated glomerular filtration rate.
∗∗∗∗C-reactive protein.
When comparing patients with low GNRI to those with high GNRI, waist circumference and calf circumference were discovered to be considerably lower in the low GNRI group. Additionally, the low GNRI group had a statistically significantly higher age. The duration of diabetes diagnosis was discovered to be considerably shorter in the low GNRI group. Among the laboratory values, total cholesterol, LDL cholesterol, eGFR, albumin, and hemoglobin levels were considerably lower in the low GNRI group. In contrast, urea, creatinine, and CRP levels were found to be considerably higher in the low GNRI group (Table 5).
4. Discussions
Sarcopenia, often linked to chronic inflammation, insulin resistance, and malnutrition, is a common comorbidity in elderly patients with T2DM. Nutritional indices, such as the GNRI, have been suggested as potential predictors of sarcopenia. Takahashi and Matsuura reported that low GNRI was associated with higher sarcopenia prevalence among elderly T2DM patients, though they did not evaluate specific threshold values [2, 9]. Consistent with these findings, we observed a higher prevalence of low GNRI among sarcopenic elderly diabetic patients. Although we applied the EWGSOP criteria instead of the Asian Working Group criteria, the direction of the association was consistent. While GNRI did not emerge as an independent predictor in multivariate analysis, our subgroup analysis reinforced the clinical relevance of GNRI < 98, a threshold commonly linked to poor nutritional status, frailty, and muscle loss in older adults.
Malnutrition and metabolic dysregulation are proposed contributors to muscle loss in diabetes. Alfaro-Alvarado FA et al. found poor glycemic control and low nutritional status were associated with reduced muscle mass [10]. In line with this, we observed lower BMI and higher prevalence of GNRI < 98 among sarcopenic patients. However, after adjustment for confounders, BMI and GNRI were not independently associated with sarcopenia, highlighting the multifactorial nature of muscle loss, where inflammation and microvascular complications may exert stronger effects.
Previous research has also linked GNRI to frailty and general health outcomes. Zhao Y et al. reported GNRI effectively identifies nutritional risk and frailty in hospitalized elderly patients [11], and Velázquez‐Alva et al. found high sarcopenia prevalence among undernourished diabetic women in nursing homes [14]. These findings support our observation that sarcopenic diabetic individuals frequently exhibit low GNRI, emphasizing the role of nutritional assessment in diabetes care.
The relationship between diabetes and sarcopenia is well established. Wang T et al. demonstrated that older adults with T2DM have a higher risk of sarcopenia and presarcopenia compared to nondiabetic individuals [15]. Although our study did not include a nondiabetic comparison group, the high prevalence of sarcopenia among our participants may reflect the influence of chronic conditions commonly associated with diabetes.
Glycemic control is another critical factor. High HbA1c levels have been associated with increased sarcopenia risk and diabetes-related complications [16, 17]. Interestingly, in our study, sarcopenic patients had lower HbA1c, which may reflect dietary restriction, reduced caloric intake, or comorbidities in advanced age.
Kim K-S et al. reported lower appendicular muscle mass in elderly men with T2DM compared to nondiabetic individuals [18]. Furthermore, both men and women with T2DM have been shown to have reduced muscle mass compared with nondiabetic controls. In our study, although the overall prevalence of sarcopenia did not differ significantly between sexes, subgroup analyses revealed sex-specific clinical patterns. In men, sarcopenia was associated with higher CRP levels, lower albumin and GNRI scores, and a greater prevalence of vascular complications, whereas in women, it was related to lower waist circumference, albumin levels, and handgrip strength, as well as a higher frequency of retinopathy. These findings suggest that the underlying mechanisms and clinical correlates of sarcopenia may differ between men and women with T2DM.
Inflammatory status has been proposed as a key factor linking nutrition and sarcopenia. Gärtner et al. reported correlations between GNRI, inflammatory markers, and hospital stay duration in elderly patients [19]. In line with this, our study revealed higher C-reactive protein levels and lower albumin concentrations among diabetic individuals with low GNRI, further supporting the association between inflammation and poor nutritional state in sarcopenic diabetics.
Treatment-related factors showed no consistent association. While some studies suggest insulin or DPP-4 inhibitors may modulate muscle loss [20, 21], Sazlina et al. found no link between insulin sensitizers and sarcopenia risk [22]. Consistent with this, our findings revealed no significant relationship between oral antidiabetic or insulin therapy and sarcopenia.
Microvascular complications further contribute to sarcopenia. Massimino et al. demonstrated a strong association between diabetic neuropathy and sarcopenia [23], and Pechmann LM et al. reported albuminuria increased sarcopenia likelihood [24]. In our cohort, sarcopenic patients exhibited higher rates of neuropathy, lower eGFR, and higher nephropathy prevalence, reinforcing the link between microvascular complications and muscle loss.
Taken together, these findings indicate that sarcopenia in elderly patients with T2DM arises from a combination of poor nutritional status, inflammation, metabolic dysregulation, and chronic complications. Assessing nutritional status using GNRI may facilitate early identification of high-risk individuals.
Limitations include the cross-sectional design and modest sample size, which preclude causal inference and limit generalizability. Unmeasured factors, such as physical activity, dietary intake, and inflammatory cytokines, could also influence results. Prospective studies are needed to clarify the temporal relationships between GNRI, glycemic control, inflammation, and sarcopenia, and to evaluate whether nutritional interventions can mitigate muscle loss in elderly diabetic patients.
5. Conclusion
Based on our findings, elderly patients with T2DM may benefit from evaluation for sarcopenia when screening for microvascular and macrovascular complications. This recommendation was derived from the observed associations in our study rather than a predefined hypothesis. Our results highlight the importance of early detection and, if possible, prevention of sarcopenia in patients with T2DM.
Funding Statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Conflicts of Interest
The author declares no conflicts of interest.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.