Type 2 diabetes mellitus (T2DM) is an important health condition in a growing ageing population, approximately 25% of people over the age of 65 years have diabetes (1). Patients with T2DM often have accelerated muscle loss and multiple comorbidities, such as hypertension (HTN); overweight/obesity; hyperlipidemia; stroke; chronic kidney disease (CKD); and cardiovascular disease (CVD) (1, 2). T2DM is characterized by insulin resistance, inflammation, increased advanced glycation end-products (AGEs), and oxidative stress (3). These characteristics may lead to losses in skeletal muscle mass, strength and function, accelerating the development of sarcopenia (3). The previous study reported, besides microvascular and macrovascular complications, sarcopenia had been described as a new complication in the elderly population with T2DM (4). Sarcopenia was an aging and disease-related syndrome characterized by progressive and generalized loss of skeletal muscle mass, low muscle strength or low physical performance, with the risk of falls, frailty, fractures, disability, hospitalization and death (5, 6).

In detecting sarcopenia, algorithms required measuring muscle strength or physical performance and skeletal muscle mass (5, 6). To date, several imaging modalities, including dual-energy X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), bioimpedance analysis (BIA) and ultrasound (US), had been developed to measure skeletal muscle mass and achieve the diagnosis of sarcopenia (7, 8). Recently, DXA has been often used to estimate muscle mass in clinical practice, and also been the only radiological tool with accepted cutoff values to diagnose sarcopenia (9). CT and MRI were considered the gold standards, but their application was mostly limited to research (7). Radiation exposure is a major limitation. And clinical CT protocols were not standardized across hospital sites. Segmentation of continuous whole body MRI is too cumbersome and expensive for clinical practice (8). US had been always regarded as a minor tool in sarcopenia, and BIA had its weakness in low precision especially in patients who have chronic illness (9, 10). However, these imaging modalities had caveats in terms of cost, possible radiation exposure, and limited accessibility for primary care and field studies.

Recently, Ken-ichiro Sasaki et al. reported that the equation based on sex, weight, and calf circumference could predict muscle mass in patients with CVD (11). Furthermore, a Japanese study developed a simple anthropometric equation, which incorporated sex, height, weight, waist circumference (WC), and calf circumference, to be potential as a reliable and an effective substitute for estimating skeletal muscle index (SMI) in the local community (12). At present, there are still many gaps in sarcopenia research, the European Working Group on Sarcopenia in Older People (EWGSOP) 2018 consensus recommended seeking accurate, affordable and simple muscle quality assessment tools, to facilitate early detection and better treatment of sarcopenia in clinical practice (5). Therefore, we aimed to determine an alternative skeletal muscle index (a-SMI) based on simple measurement indexes, and to validate the diagnostic value of new diagnostic approach for sarcopenia in elderly patients with T2DM.

In the current study, we proposed a model to estimate d-SMI in positive screening population, which was calculated by a regression formula including the values of the subject’s sex, BMI, 25 - (OH) VitD, and HTN history, based on stepwise multivariate binomial logistic regression analysis. The new diagnostic approach developed in this study, was composed of handgrip strength, gait speed, and the a-SMI, could be used to supplement the algorithm for sarcopenia diagnosis in elderly patients with T2DM. For the diagnosis of sarcopenia, the prevalence of sarcopenia diagnosis by the new diagnostic method was 40.4%, and that was present in 36.3% according to the recommended diagnostic algorithm of the AWGS 2019. This indicated that the two criteria were in close agreement. And the a-SMI held potential as a reliable and an effective substitute in the absence of the d-SMI.

In our equation, a higher BMI level was associated with lower d-SMI. Previous studies reported that underweight subjects were at a higher risk of low skeletal muscle (14). A retrospective cross-sectional study included community-dwelling adults over 60 years of age suggested that obesity might have a protective effect in sarcopenic individuals (15). Several explanations had been proposed as to why obesity is not harmful to older adults (15). Overweight or obesity might be associated with a better supply of vitamins and other nutrients that ensure proper functioning (15). In addition, a higher BMI was associated with greater BMD, it might provide against osteoporotic fractures (16). Another important benefit of obesity in older adults was its association with higher levels of estrogen in this population (15). The estrogen produced by adipose tissue might exert protective effects on various organs through the effect of secretion. A Japanese study found elderly diabetes patients with low BMI and high body fat mass may be more likely to develop sarcopenia (17). Without taking body fat into account, subjects with high BMI tend to have more lean body mass (18, 19). Therefore, BMI might reflect lean mass in elderly diabetes patients (17).

Vitamin D played an important role in bone mineralization and musculoskeletal health (20). Our results had shown that 25 - (OH) VitD was significantly decreased in elderly patients with type 2 diabetic sarcopenia, and it was independent risk factor for d-SMI. It implied that 25 - (OH) VitD may play an important role in sarcopenia. The results of our study were in line with other studies where 25 - (OH) VitD was associated with muscle mass and function, increased the risk of sarcopenia in the elderly (21–23). A Korea study reported that sarcopenia was significantly associated with hypertension, particularly in the subjects with DM, and revealed that appendicular muscle mass (ASM) was independently related to SBP (24). HTN history in our study had adverse effects on d-SMI. Four possible mechanisms might explain the link between ageing muscle and HTN, including insulin resistance, inflammation, the relative paucity of myokines and alterations within the renin-angiotensin-aldosterone system (RAAS) (24–27).

Anagnostis et al. reported that the risk of sarcopenia were increased 1.72 -fold (95% CI: 1.1 ~ 2.69; p = 0.017) in male and 1.46 -fold (95% CI: 0.94 ~ 2.25; p = 0.08) in women with T2DM, and this difference between genders was not significant (28). In this study, the prevalence of sarcopenia in the T2DM patients aged 60 years was 19.7% for males and 16.6% for females. Males in our study had adverse effects on d-SMI. Testosterone levels in men decline with age, adversely affecting the distribution of muscle and adipose tissue (29). Earlier study had shown that men have more lean mass, and women have more fat mass. As people get older, men were more likely to accumulate adipose tissue around the trunk and abdomen, while women usually accumulate adipose tissue around the hips and thighs (30).

For the diagnosis of sarcopenia, it was necessary to measure grip strength, gait speed, and d-SMI. Grip strength and gait speed can be easily measured with small and simple instruments. We propose the a-SMI -based on gender, obesity status, 25-(OH) VitD, and HTN history - could be used in the absence of the d-SMI. Sarcopenia was diagnosed by the cutoff value of the a-SMI. Compared with MRI, CT and DXA, a-SMI can be performed in a small infirmary at a lower cost without radiation hazards. We did not define formulas by sex because we did not think it appropriate to define formulas based on data from a small number of men and women with sarcopenia. Nonetheless, the accuracy of the diagnosis of sarcopenia needs to be verified with surrogate indices and cut-off values in other populations.

There were some limitations in our study. First, due to the absence of CT and MRI (gold standards) for sarcopenia diagnosis, DXA recommended by AWGS 2019 was used in this study. The second concerns the formula, which calculated an abstract dimensionless proxy with quite different cut-off values, did not estimate muscle mass in kg or not a SMI in kg/m². Third, it was a single-center study with a small population, limiting the ability to apply the result to the other ethnic groups, which needs to be further verified in other groups and institutions.

The present study demonstrates that the a-SMI - based on gender, obesity status, 25-(OH) VitD, and HTN history - can be used in the absence of the d-SMI to supplement the algorithm for sarcopenia diagnosis in elderly patients with T2DM. We believe that this new diagnostic approach of sarcopenia may be a useful tool for early prevention and early treatment of elderly T2DM patients with sarcopenia, thereby mitigating the adverse outcomes of T2DM patients due to sarcopenia.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

This study was approved by the ethics committee of the First Hospital of Qinhuangdao. All subjects provided written informed consent before study initiation.

BL: Conceptualization, Funding Acquisition, Resources, Supervision, Writing - Review & Editing. LL: Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing - Original Draft. All authors contributed to the article and approved the submitted version.