Introduction
Type 2 diabetes (T2D) is a progressive disease characterized by insulin resistance and continuous loss of endogenous insulin secretion [1]. Furthermore, T2D is associated with sarcopenia, which results in the loss of whole-body homeostasis and decline in physical function [2]. Sarcopenia-derived muscle weakness is consistently associated with deterioration of glucose metabolism in patients with diabetes, even among well-nourished subjects [3, 4]. Relative handgrip strength (RHGS) has been proposed as a diagnostic tool for assessing muscular strength and quality, including in overweight individuals [5]. In this clinical study, the relationship between muscle strength and quality and low-density lipoprotein cholesterol (LDL-C), random triglyceride (TG), and high-density lipoprotein cholesterol (HDL-C) levels was studied in patients with T2D to search for a new factor affecting RHGS in patients with T2D as the relationship between RHGS and LDL-C in patients with T2D is inconclusive.
Materials and methods
Participants
Our study protocol was reviewed and approved by the Institutional Review Board of Hoshi-iin as 3–1 (March 31, 2021). Written informed consent was obtained from each participant.
We excluded participants who had been diagnosed with type 1 diabetes (n = 1). Also, patients with orthopedic diseases such as chronic rheumatoid arthritis or cerebrovascular diseases with paralysis were excluded (n = 1 and n = 2, respectively).
Patients consistently visited the hospital for follow-up examinations once a month. Using the same random blood samples as previously reported, the patients’ lipid profiles, plasma glucose levels, and glycated hemoglobin (HbA1c) levels were measured [6]. When patients visited the hospital, a registered nurse and registered dietician advised on the necessary dietary and lifestyle modifications.
Definition of T2D
Diabetes is defined as a fasting plasma glucose of 126 mg/dL or greater and/or a 2-h glucose level of 200 mg/dL or greater during a 75-g OGTT [7]. Anti-glutamic acid decarboxylase antibody was negative and insulin secretion was not depleted in all participants.
Handgrip strength and RHGS measurement
Using a digital grip strength dynamometer (Model T.K.K 5401; Takei Scientific Instruments Co., Tokyo, Japan, measurement range: 5.0–100.0 kg), handgrip strength was measured in each hand three times [8]. The participants were instructed to hold the dynamometer with the second proximal interphalangeal joint of the hand flexed at 90° to the handle and squeeze the handle as hard as they could in the standing position (elbow extension status). The participants rested for at least 30 s after each measurement. The maximum value of the three measurements was used [9].
RHGS was used for assessing muscular strength and quality. RHGS was calculated by dividing the absolute handgrip strength by body mass index (BMI) [10].
Statistical analysis
All statistical data were analyzed using the SPSS software (version 10.0, SPSS Inc., Chicago, IL, USA). All numerical values are expressed as mean ± standard deviation. Using the stepwise method, multiple regression analysis was conducted with a software program. We calculated Pearson correlation coefficient to estimate the linear correlation between variables.
Results
Participant characteristics
This study enrolled 68 patients with T2D who visited our hospital in April 2022. Patient characteristics are shown in Table 1. The majority of the participants were men, accounting for 71.5%. The median values of the measured parameters were as follows: age 67 (range 24–94) years, body weight 64.1 (range 45.7–136.2) kg, BMI 24.35 (range 17.9– 42.2) kg/m2, HbA1c level 7.4% (range 5.8–12.8), random TG level 139 (range 53–493) mg/dL, HDL-C level 52.5 (range 36–119) mg/dL, LDL-C level 104.8 (range 30–174) mg/dL.
|
Median value |
Range |
|
|
Age [years] |
67 |
24–94 |
|
Physical activity level [METs/h/week] |
10.1 |
3.0–20.8 |
|
Estimated glomerular filtration rate [mL/min/1.73 m2] |
57.0 |
33.0–93.0 |
|
Systolic blood pressure [mmHg] |
123.5 |
93–191 |
|
Diastolic blood pressure [mmHg] |
69.0 |
47–101 |
|
Body weight [kg] |
64.1 |
45.7–136.2 |
|
Body mass index [kg/m2] |
24.35 |
17.9– 42.2 |
|
Glycated hemoglobin (HbA1c) [%] |
7.4 |
5.8–12.8 |
|
Random triglyceride (TG) [mg/dL] |
139 |
53–493 |
|
High density lipoprotein cholesterol (HDL-C) [mg/dL] |
52.5 |
36–119 |
|
Low density lipoprotein cholesterol (LDL-C) [mg/dL] |
104.8 |
30–174 |
|
Duration of type 2 diabetes (T2D) [years] |
16.0 |
4–45 |
Proportion of patients prescribed with antidiabetic, antihypertensive, and antihyperlipidemic medications
The proportion of patients prescribed antidiabetic medications are shown in Table 2. The proportion of prescribed antidiabetic medications was as follows: sodium-glucose cotransporter 2 inhibitors, biguanides, insulin, sulfonylureas, dipeptidyl peptidase-4 inhibitors, α- glucosidase inhibitors, GLP-1 receptor analogs, and glinides were prescribed in 40.5%, 43.2%, 54.1%, 2.7%, 37.8%, 29.7%, 27.0%, and 48.6% of patients, respectively, while no thiazolidinedione was prescribed.
|
Sodium glucose cotransporter inhibitors (%) |
40.5 |
|
Biguanides (%) |
43.2 |
|
Insulin (%) |
54.1 |
|
Sulfonylureas (%) |
2.7 |
|
Dipeptidyl peptidase-4 inhibitors (%) |
37.8 |
|
α-glucosidase inhibitors (%) |
29.7 |
|
Glucagon-like peptide 1 analogs (%) |
27.0 |
|
Glinides (%) |
48.6 |
|
Thiazolidinedione (%) |
0 |
Antihypertensive and antihyperlipidemic drugs were prescribed in 72.2% and 61.1% of patients, respectively.
Analysis of multiple comparisons for factors affecting RHGS
RHGS was 1.47 ± 0.40 kg/BMI. Stepwise multiple regression analysis demonstrated that the LDL-C was a significant determinant of RHGS and not TG and HDL-C (r = 0.349, p < 0.001, r = 0.130, p = not significant, r = 0.084, p = not significant, respectively). Thus, RHGS correlated with the LDL-C level and the result was shown in Figure 1.
Discussion
Recently, handgrip strength (HGS) has emerged as a substitute for muscle strength measurement owing to its convenience and economic advantages. Hence, various organizations defining sarcopenia accepted HGS as one of the most reliable tools to establish a diagnosis of sarcopenia [11–13]. However, the cutoff values of HGS defining low muscle strength differed among different studies. A review paper on sarcopenia indicated that muscle strength measured by HGS should be stratified by BMI [14]. With this data, several studies have revealed that the relative HGS adjusted for BMI (RHGS) instead of absolute HGS are inversely related to numerous age-related diseases, such as metabolic syndrome, diabetes mellitus, cardiovascular disease, and chronic kidney disease [15, 16]. In recent nationwide population-based studies, RHGS demonstrated a stronger correlation with cardiovascular biomarkers than absolute HGS and dominant HGS [17, 18]. Higher RHGS was considerably associated with a lower systolic blood pressure, TG, plasma insulin and glucose, and HDL-C levels [17].
However, any correlation between RHGS and random TG and HDL-C level was not observed in our study. Thus, our results are different from previous paper reporting that the HDL-C and TG levels were determinant factors for RHGS in the participants from the National Health and Nutrition Examination Survey [17]. Conversely, limited literature exists regarding whether RHGS correlates with the LDL-C level.
Interestingly, our study demonstrated that a positive correlation between RHGS and LDL-C level exists. However, in another previous paper, RHGS was negatively associated with LDL-C level in middle-aged and elderly community-dwelling women [10]. Compared to our results, these discrepancies may be secondary to the differently selected participants. We examined patients with T2D alone and the majority of the participants were men, accounting for 71.5%. On the other hand, the previous studies analyzed participants from National Health and Nutrition Examination Survey and middle-aged women. Also, the sample size was different from our study.
Our study has few limitations that merit consideration. First, the omission of comprehensive covariate adjustment in our analysis, including variables such as age, gender, duration of diabetes, and BMI, restricts our ability to fully account for potential confounding effects. Second, the cross-sectional design prohibits the establishment of causal relationships. Third, the analysis of nominal variables, such as gender, using traditional correlation methods presents challenges due to linearity assumptions, and while biserial correlation would be ideal, software constraints limited its implementation. Fourth, while our study focuses on the Japanese population, variations in socioeconomic status, cultural diversity, and healthcare access may limit the generalizability of our findings across all segments of the population. Finally, the sample size was relatively small (n = 68) and the majority of the participants were men (71.5%). Therefore, this study may be exploratory in nature without adequate power. These limitations underscore the need for cautious interpretation and highlight avenues for future research with more comprehensive datasets and study designs.
Despite these limitations, this study can suggest the following clinical implications. In the secondary prevention program of cardiovascular disease in patients with T2D, the target range of LDL-C level is below 70 mg/dL [19]. Based on our result, an extremely lower LDL-C level may cause a reduced RHGS leading to an increased risk of sarcopenia. Furthermore, as an adverse effect of cholesterol-lowering statin, an increased risk of T2D is well recognized. This adverse effect may be secondary to a reduced RHGS by cholesterol-lowering statin. When clinicians reduce the LDL-C level using a cholesterol-lowering drug, they are required to monitor the RHGS including the lipid profile to detect the early sign of sarcopenia in patients with T2D. As an extremely low LDL-C may cause a reduced RHGS leading to an increased risk of sarcopenia, clinicians are required to monitor RHGS stringently.
Article information
Data availability
The datasets generated or analyzed during this study are available from the corresponding author on reasonable request.
Ethics statement
This study complies with the guidelines for human studies in accordance with the World Medical Association Declaration of Helsinki. The subjects have signed written consent for the publication. This study protocol was reviewed and approved by the review boards of Hoshi-iin as 3-1 (March 31, 2021).
Author contributions
Shuichi Okada, Tsugumichi Saito, Tetsuro Andou, and Kihachi Ohshima designed the clinical study. Shuichi Okada and Hiroto Hoshi performed the clinical study. Kikkawa Koji, Atsushi Isoda, Junichi Okada, Kazuya Okada, Eijiro Yamada, and Shuichi Okada collected data and attended every meeting to discuss this project. Junichi Okada, Yasuyo Nakajima, and Shuichi Okada prepared the manuscript. Shuichi Okada and Yasuyo Nakajima performed statistical analysis.
Funding
No funding was received for this study.
Conflict of interest
The authors declare no conflict of interest.