This study was a single-center, cross-sectional, observational study.

The participants were 107 young to middle-aged adults with T2DM younger than 65 years who were admitted to the Department of Metabolic Medicine, Kumamoto University Hospital, for educational purposes and who requested rehabilitation by the Department of Metabolic Medicine. The study period was from April 2014 to March 2022, and patients were selected retrospectively based on their medical records. The exclusion criteria were patients with preexisting or primary diseases that could affect the skeletal muscle mass index (SMI) by bioelectrical impedance analysis, including patients (1) undergoing cancer treatment, (2) with neurological diseases, (3) with edema, and (4) with internal metal stents or pacemakers implanted in their bodies. The control group consisted of patients who received rehabilitation during their hospitalization at our hospital and did not have diabetes; they were selected at comparable eligible ages, and those who met the above exclusion criteria were excluded. Data for all patients were taken from the first measurement taken after admission.

Of the 250 patients with T2DM who requested rehabilitation by the Department of Metabolic Medicine during the period mentioned above, patients younger than 65 years were included and selected based on the inclusion criteria described above. A total of 56 patients were excluded due to missing data from the muscle mass measurement device, and an additional 87 patients were excluded because they were undergoing cancer treatment, or because of the presence of metals in their bodies, such as pins and screws. Finally, data from 55 men and 52 women were analyzed (Figure 1).

This study defines diabetes as exposure and outcome as skeletal muscle mass, which was the main skeletal muscle mass measured using the InBody 720 and InBody S10 (InBody Japan Inc) as the multifrequency bioelectrical impedance analysis method. InBody measurements were performed in the same limb position, using the same procedure, and were performed by a person skilled in operating the equipment. Skeletal muscle mass loss was defined as SMI <7.0 kg/m² in men and <5.7kg/m² in women based on Asian Working Group on Sarcopenia (AWGS) criteria [17]. The assessment items were age, sex, BMI, SMI, physical function (grip strength, comfortable walking speed, and one-leg standing time with eyes opened), medical history, insulin therapy, blood data, pulse wave velocity (PWV), and diabetes-related complications (retinopathy, renal impairment, or neuropathy).

Data on age, sex, BMI, and nutritional status were collected from medical records. BMI was calculated as weight (kg) divided by the square of height (m). Serum albumin and total cholesterol levels were extracted from the blood data as indicators of nutritional status, and estimated glomerular filtration rate levels were extracted from medical records to assess renal function. Blood samples were collected after overnight fasting at admission.

Physical function was assessed based on grip strength, walking speed, and one-leg standing time. Grip strength was measured twice (once on each side), and the best value was used. The 10-m walking speed was measured using a stopwatch, and the test ended when the leading foot stepped on or crossed the 10-m starting line. The test was performed at normal walking speed, measured twice, and the better value was used. One-leg standing time was measured as the time that one leg was raised about 5 cm from the floor, and the better value of the 2 measurements, both left and right, was used. The cutoff values for grip strength and walking speed were also based on those proposed by AWGS as follows: grip strength <26 kg for men and <18 kg for women, and walking speed 0.8 m/s for men and women [17]. In the one-leg standing time, the standard value was 30 seconds or more based on previous studies [18].

To assess glycemic control status, data on hemoglobin A_1c (HbA_1c; glycated hemoglobin), history of diabetes mellitus, and treatment with insulin or oral medications were extracted. History of diabetes was defined as the period from the diagnosis of diabetes mellitus. Furthermore, an ophthalmologist diagnosed diabetic retinopathy as simple retinopathy, preproliferative retinopathy, or proliferative retinopathy. Diabetic nephropathy was graded in severity based on urinary protein or albumin levels and estimated glomerular filtration rate levels and staged from stage I to stage V. Patients were identified at admission. Diabetic peripheral neuropathy was defined as the presence of diabetes mellitus as an essential condition and peripheral neuropathy other than diabetic neuropathy could be ruled out or loss of bilateral Achilles tendon reflexes was defined as having diabetic peripheral neuropathy. Moreover, arteriosclerosis is a complication of diabetes-related vascular diseases, and PWV was extracted to evaluate it. PWV, a test to determine the degree of arterial stiffness, measures the speed at which the heartbeat is transmitted through the arteries to the hands and feet, with higher readings indicating stiffer blood vessels and more advanced arterial stiffness [19].

All statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University), which is a graphical user interface for R (The R Foundation for Statistical Computing). More precisely, it is a modified version of R commander designed to add statistical functions frequently used in biostatistics. The Kolmogorov-Smirnov test was used to assess the normality of the distribution of variables in each group. To test for differences between the groups with and without diabetes, normally distributed data were analyzed using the 2-tailed t test, whereas nonnormally distributed data were analyzed using the Mann-Whitney U test. Univariate logistic regression analysis was performed to determine the variables associated with SMI. In the multivariate analysis, we set age as a confounding variable and BMI as a mediator. Based on the univariate analysis, clinical findings that were statistically significantly associated with SMI were set as exposures, and the final model was constructed while accounting for multicollinearity. Missing data were excluded at the time of collection and are not included in the statistics. Statistical significance (P value) and odds ratios with 95% CI were calculated. In addition, sensitivity analysis was conducted by changing explanatory variables in the multivariate analysis. All results were considered statistically significant at P<.05.

This study was approved by the Ethics Committee of the Graduate School of Life Sciences Research at Kumamoto University (ethics 2366) and complied with the ethical regulations of the Declaration of Helsinki (as revised in Fortaleza, Brazil, October 2013). All survey items and images used in this study were those used in routine medical practice and were conducted so that individuals could not be identified.

As for informed consent, the physician in charge of the medical care concerned conducted the research in accordance with the “Declaration of Helsinki” and the “Ethical Guidelines for Medical Research Involving Human Subjects” based on a separately specified consent document prior to conducting the research. Participation in the study was conducted on an opt-out basis, with a request for cooperation in the clinical research described on the hospital’s website. The open document was published on the website of the Department of Rehabilitation Medicine. The opportunity to refuse participation was guaranteed by stating that if the patient did not wish to cooperate in the research, he or she would be contacted and would not be disadvantaged in any way, with no impact on his or her medical treatment, even if he or she refused to participate in the study. For secondary analyses that use existing data with primary consent, the initial consent covers the secondary analysis without additional consent.

This study is one of the few to focus on skeletal muscle mass loss in young to middle-aged adult patients with diabetes. The results showed that a certain percentage of middle-aged patients with diabetes also had decreased skeletal muscle mass, resulting in decreased muscle strength and physical ability compared with healthy individuals. Furthermore, middle-aged men with diabetes had higher rates of skeletal muscle mass loss, muscle weakness, and loss of physical ability than women with diabetes.

According to the AWGS 2019, sarcopenia is defined as a loss of skeletal muscle mass and a loss of muscle strength or physical capacity, while severe sarcopenia is defined as a loss of skeletal muscle mass plus a loss of both muscle strength and physical capacity; moreover, severe sarcopenia is defined as a loss of both muscle strength and physical performance in addition to a loss of skeletal muscle mass. The results of this study suggest that middle-aged patients with diabetes, especially men, have a higher risk for loss of muscle mass and decline in both muscle strength and physical function than those without diabetes. To elucidate the relationship between diabetes and sarcopenia, skeletal muscle mass plays a substantial role in peripheral blood glucose uptake and use, and its reduction in sarcopenia results in compromised glucose tolerance due to diminished peripheral blood glucose uptake. Similarly, reduced physical activity stemming from loss of muscle mass also contributes to impaired glucose tolerance, exacerbating diabetes and leading to difficulty in controlling T2DM. Thus, T2DM promotes the development of sarcopenia, which contributes to the onset and worsening of diabetes, coupled with diabetic complications, leading to a vicious cycle of decreased physical activity, a secondary decrease in skeletal muscle mass, and worsening diabetes [20].

Previous studies have reported that older adult patients with diabetes are more prone to age-related loss of skeletal muscle mass than healthy individuals and that sarcopenia occurs several years earlier in patients with diabetes than in healthy individuals [21]. Furthermore, studies in mice have shown that hyperglycemia, a central disease of diabetes, promotes muscle atrophy via the WWP1/KLF15 pathway and that in mice lacking KLF15, specifically in the skeletal muscle, hyperglycemia-induced muscle atrophy is suppressed [4]. Moreover, it has been reported that terminal glycation products, a major cause of diabetic vascular complications, accumulate with chronic hyperglycemia and aging in various tissues; additionally, their accumulation contributes to a decline in muscle mass and strength, possibly leading to sarcopenia and dynapenia in T2DM [22]. Similar to previous studies on older adult patients with diabetes, this study found that skeletal muscle mass and strength loss occur earlier in young to middle-aged adult patients with diabetes, especially in men, than in healthy individuals. In addition to age, male sex, low BMI, elevated HbA_1c, diabetic nephropathy, and low serum albumin concentration have been reported as risk factors associated with low muscle strength in patients with diabetes [6]. In contrast, other studies have reported that diabetic polyneuropathy contributes to lower limb muscle weakness in older patients with T2DM [19]. In this study, logistic regression analysis showed that BMI and peripheral neuropathy were associated with skeletal muscle mass loss in middle-aged adult patients with T2DM, similar to the results in older adult patients with T2DM [23]; however, there was no association with HbA_1c or diabetic complications. Furthermore, Korean older adults with T2DM had a prevalence of skeletal muscle loss of 57.6% in men and 7.1% in women. The association between T2DM and skeletal muscle loss appeared more prominent in men, with the risk of muscle loss being approximately 2 to 4 times higher in older adults with T2DM than in healthy controls [24]. In this study, the prevalence of skeletal muscle loss in young to middle-aged individuals with T2DM was 18.2% in men and 7.7% in women, suggesting that even in younger populations, T2DM is associated with an increased risk of skeletal muscle mass loss, particularly in men.

This study showed no differences in skeletal muscle mass or muscle strength between middle-aged adult women with T2DM and healthy controls. This outcome was anticipated owing to the younger average age and elevated BMI of the women participants in this study. Moreover, the limited number of control participants used for comparison is also believed to have influenced this result. Nonetheless, despite preserving skeletal muscle mass and strength, the participants notably underperformed, compared with healthy controls, in terms of physical performance and balance function. This indicates that the quality of skeletal muscle may have been compromised. Therefore, the prospect of dynapenia occurring in women was anticipated. Although many previous studies have compared sarcopenia-related factors, such as skeletal muscle mass, muscle strength, and walking speed, few have examined balance function, which makes this study significant. Furthermore, we found that the same functional decline in both men and women differed between those with and without loss of skeletal muscle mass and strength.

This study had some limitations. First, owing to the nature of the study, the number of participants was inadequate, especially in the female control group. This was due to the fact that this was a single-center, backward-looking study, which limited the selection of participants. Moreover, because this was a retrospective study, there were many missing data points, which made it difficult to select the participants.

Finally, this study aimed to elucidate the presence of skeletal muscle mass and muscle weakness in young and middle-aged patients with diabetes. The study also sought to identify associated factors that will be applied in clinical education and exercise therapy for patients with diabetes. Importantly, this information should be considered from an early stage for the purpose of preventive rehabilitation. Therefore, this study shows that young to middle-aged adult patients with diabetes exhibit reduced skeletal muscle mass, muscle weakness, sarcopenia, and loss of physical performance, proving the importance of exercise therapy and the need for strength training. We believe this information can be applied to patient education in future clinical practice. Moreover, as a future prospect, we would like to develop this study further to examine sex differences and develop better teaching and more effective strength training methods.

In conclusion, young to middle-aged adult patients with diabetes, especially men, have lower skeletal muscle mass than those without diabetes and may experience further decline in physical function. Therefore, early and detailed assessment of muscle mass and strength as well as physical function will be necessary even in young and middle-aged individuals.