The association between time in range with sarcopenia and its components in older patients with type 2 diabetes mellitus

Abstract

Time in range (TIR) is a new marker for blood glucose management, but its relationship with sarcopenia and its components requires further investigation. This study aims to investigate the association between TIR and sarcopenia and its components in older patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included 310 hospitalized patients aged ≥ 60 years with T2DM. Continuous glucose monitoring (CGM) was used to assess TIR, and sarcopenia was diagnosed according to the 2019 criteria of the Asian Working Group on Sarcopenia, including indicators such as skeletal muscle mass index (SMI), handgrip strength, and physical performance. The relationships between TIR and sarcopenia and its components were analyzed using a logistic regression model, a linear regression model, and a restricted cubic spline model. The prevalence of sarcopenia was 32.3%. After adjusting for multiple factors, each 10% increase in TIR was associated with a 17% reduction in sarcopenia risk (odds ratio [OR] and 95% confidence interval [CI] = 0.83 [0.74–0.93], P = 0.001). Patients with TIR ≥ 70% had a 62% lower risk of sarcopenia compared to those with TIR < 50% (OR and 95%CI: 0.38 [0.19–0.74], P = 0.005). TIR showed a linear positive correlation with SMI and a nonlinear correlation with handgrip strength; however, it was not significantly associated with physical performance. Higher TIR is associated with higher muscle mass and handgrip strength, as well as a lower incidence of sarcopenia. For older adults with type 2 diabetes who have a low TIR, caution should be exercised regarding their elevated risk of developing sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-57109-w.

Introduction

Sarcopenia is a progressive syndrome characterized by age-related loss of skeletal muscle mass, strength, and function, adversely affecting health and quality of life in older adults^1–3. Its prevalence is substantially higher among hospitalized older adults than in community settings^4,5 and is further increased in patients with type 2 diabetes mellitus (T2DM)⁶. As diabetes continues to pose a major global public health burden^7–9, identifying glycemic indicators associated with sarcopenia in high-risk hospitalized older adults with T2DM is clinically important.

Blood glucose levels are a direct driver of diabetes complications. Hyperglycemia increases the risk of microvascular and macrovascular complications^10,11, while both long-term and short-term patterns of blood glucose fluctuations are associated with complication risk^12,13. Glycated hemoglobin (HbA1c) is widely used to assess average blood glucose levels. Studies have shown that HbA1c is associated with both muscle mass and sarcopenia^14–17. However, the primary limitations of HbA1c include its inability to capture intraday blood glucose fluctuations, its failure to detect asymptomatic hypoglycemic events, and its susceptibility to hemoglobin lifespan and individual variability^18,19. Time in range (TIR) serves as a novel indicator for glycemic management, providing more detailed information on the quality of blood glucose control, including the frequency of time above range and time below range, thereby addressing the limitations of traditional HbA1c¹⁸.

Previous studies have showed that TIR provides a more comprehensive reflection of blood glucose fluctuations, thereby enabling more accurate prediction of muscle health risks^20,21. However, the association between TIR and sarcopenia requires further investigation. This study utilized continuous glucose monitoring technology to collect TIR data, examined the association between TIR and sarcopenia and its components in older adults with T2DM, and further analyzed the dose–response relationship. This research aims to provide evidence for identifying and managing sarcopenia risk in individuals with T2DM.

Methods

Study population

This cross-sectional study targeted patients with T2DM hospitalized in the Geriatric Medicine Department of the Third People’s Hospital of Yunnan Province, China, from March 2024 to March 2025. Included patients aged ≥ 60 years with T2DM, without acute diabetic complications, and whose glucose-lowering regimen remained unchanged over the past 3 months. Exclusion criteria were (1) patients with type 1 diabetes; (2) patients with New York Heart Association Class IV heart failure or advanced malignant tumors; (3) patients receiving glucocorticoid therapy; (4) patients with severe mobility impairment unable to cooperate with sarcopenia assessment. A total of 310 patients were ultimately included in the study. All participants received and signed informed consent forms, and the study was approved by the Third People’s Hospital of Yunnan Province ethics committee (2023KY103). This study has been registered with the China Clinical Trial Registry (Registration number: ChiCTR2400091340) and strictly adheres to the ethical principles of the Declaration of Helsinki.

Assessment of TIR

Within the first three days of admission, all enrolled patients wore the CGM system (Meiqi, Model: RGMS-II) for the subsequent three days. This continuous glucose monitoring system was used to obtain TIR. TIR, defined as glucose levels between 70 and 180 mg/dL, was calculated as the percentage of time that CGM glucose readings fell within the target range. While wearing the CGM system device, patients maintained their normal diet, exercise habits, and glucose management regimen.

Assessment of sarcopenia

The diagnosis of sarcopenia was based on skeletal muscle mass, muscle strength, and physical performance. According to the 2019 criteria of the Asian Working Group for Sarcopenia²², sarcopenia is diagnosed when a subject exhibits low skeletal muscle mass accompanied by either low muscle strength or low physical performance. This study employed bioelectrical impedance analysis to measure changes in the electrical impedance of tissue cells via bioelectrical sensors, thereby estimating an individual’s total body muscle mass. Muscle mass reduction is defined as skeletal muscle mass index (SMI) < 7.0 kg/m² for male and < 5.7 kg/m² for female. The CAMRY dynamometer (Model: EH101) was used to assess muscle strength by measuring handgrip strength (kg). Each participant underwent two handgrip strength tests per hand, with the maximum value recorded. Low muscle strength was defined as a maximum handgrip strength of < 28 kg for male and < 18 kg for female. Physical performance was assessed based on gait speed and 5-time chair stand test. A straight line 12 m long was marked on level ground, indicating the starting point and the 3-, 9-, and 12-m positions. The subject walked from the starting point, and the time to cover the distance from 3 to 9 m was recorded. The test was performed twice, and the fastest gait speed was recorded. The patient sat on a 46-cm-high chair with arms crossed over the chest and completed five stand-up and sit-down movements as quickly as possible. This test was performed two times, with a one-minute rest between each trial. The shortest time from the two trials was used as the test result. Participants were considered to have low physical performance when their maximum gait speed was < 1 m/s or 5-time chair stand test ≥ 12 s.

Covariates

The selection of covariates was based on prior literature regarding risk factors for sarcopenia in older adults with T2DM and on clinical considerations. The covariates in this study included demographic information, lifestyle habits, chronic disease status, and biomarkers, all of which were obtained from medical records. Demographic information encompassed age, gender, and marital status. Lifestyle habits included smoking and alcohol consumption. Chronic disease conditions consisted of coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, and malnutrition. Biomarkers included albumin (ALB), triglycerides (TG), total cholesterol (TC), and body mass index (BMI). Venous blood samples were collected from all recruited patients in the morning after a 10-h fast for the measurement of ALB, fasting plasma glucose (FPG), HbA1c, TG, TC, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C).

Statistical analysis

Referencing previous studies^23,24, we converted TIR into a categorical variable using 50% and 70% as cutoff points, dividing participants into the following three groups: Q1 (< 50%), Q2 (50%-69%), and Q3 (≥ 70%). We analyzed the relationship of TIR (as both a continuous and categorical variable) with sarcopenia, SMI, handgrip strength, the 5-time chair stand test, and gait speed.

Continuous variables following a normal distribution are represented by mean ± standard deviation. Continuous variables with skewed distributions are represented by median and interquartile range. Categorical variables are presented as counts and percentages. Baseline characteristics of participants in the sarcopenia group and non-sarcopenia group were compared using t-tests, chi-square tests, and nonparametric tests. Logistic regression was used to estimate the odds ratio (OR) and its 95% confidence interval (CI) for the association between TIR and sarcopenia. We constructed two models: model 1 was a univariate analysis; model 2 adjusted for gender, age, marital status, smoking status, alcohol consumption, coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, malnutrition, ALB, TG, TC, and BMI. A linear regression model was employed to analyze the relationship between TIR and SMI, handgrip strength, the 5-time chair stand test, and gait speed. To investigate potential non-linear relationships between TIR with sarcopenia and its components, we employed trend tests and restricted cubic spline (RCS) models for validation. To further assess the stability of the results, we conducted subgroup analyses among individuals differing in age, gender, coronary heart disease, chronic kidney disease, malnutrition, and body mass index status.

All the analyses were performed with the statistical software Stata/MP version 18.0 (StataCorp LP, College Station, TX, USA) and Free Statistics software versions 2.1.1. The level of statistical significance was set at p < 0.05 (two-sided).

Results

Baseline characteristics of study participants

Table 1 shows the baseline characteristics of participants grouped according to sarcopenia status. This study enrolled 310 participants with a mean age of 76.6 ± 8.8 years, of whom 59.0% were female; 100 participants were diagnosed with sarcopenia. Compared with participants without sarcopenia, the sarcopenic cohort was more likely to exhibit the following characteristics: older age, higher alcohol consumption, elevated HbA1c levels, and lower BMI and TIR (all P values < 0.05).

Table 1.

Baseline characteristics of participants.

	Total (n = 310)	No Sarcopenia (n = 210)	Sarcopenia (n = 100)	P
Gender, n (%)				0.214
Female	183 (59.0)	129 (61.4)	54 (54.0)
Male	127 (41.0)	81 (38.6)	46 (46.0)
Age, year	76.6 ± 8.8	75.6 ± 8.8	78.8 ± 8.4	0.003
Marital, n (%)				0.939
Other	97 (31.3)	66 (31.4)	31 (31.0)
Married	213 (68.7)	144 (68.6)	69 (69.0)
Smoking status, n (%)				0.138
Never smoked	244 (78.7)	171 (81.4)	73 (73.0)
Former smoker	27 ( 8.7)	14 (6.7)	13 (13.0)
Current smoker	39 (12.6)	25 (11.9)	14 (14.0)
Alcohol consumption, n (%)				0.046
Never or rarely	275 (88.7)	192 (91.4)	83 (83.0)
Less than once a month	6 ( 1.9)	2 (1.0)	4 (4.0)
More than once a month	29 ( 9.4)	16 (7.6)	13 (13.0)
Chronic disease status, n (%)
Coronary heart disease	125 (40.3)	87 (41.4)	38 (38.0)	0.565
Chronic obstructive pulmonary disease	39 (12.6)	25 (11.9)	14 (14.0)	0.154
Chronic kidney disease	44 (14.2)	28 (13.3)	16 (16.0)	0.529
Malnutrition	66 (21.3)	41 (19.5)	25 (25.0)	0.271
Biomarkers
Albumin, g/l	41.6 ± 5.6	42.0 ± 5.6	40.8 ± 5.6	0.084
Triglycerides, mg/dl	147.5 (105.6, 220.5)	148.8 (106.3, 220.5)	146.1 (105.4, 220.5)	0.988
Total cholesterol, mg/dl	165.4 ± 44.4	165.3 ± 38.5	165.6 ± 55.4	0.951
Body mass index, kg/m2	23.5 ± 3.2	24.2 ± 3.2	22.3 ± 2.9	< 0.001
HBA1c, %	7.7 ± 1.6	7.6 ± 1.5	8.0 ± 1.8	0.018
5-time chair stand test, s	13.9 ± 4.6	13.7 ± 4.3	14.4 ± 5.1	0.173
Handgrip strength, kg	22.5 ± 7.5	23.4 ± 7.5	20.7 ± 7.2	0.003
Gait speed, m/s	1.1 ± 0.4	1.1 ± 0.4	1.0 ± 0.4	0.016
Skeletal muscle mass index	6.5 ± 0.9	6.8 ± 0.8	5.8 ± 0.8	< 0.001
Time in Range, %	64.0 ± 25.2	67.4 ± 24.0	56.9 ± 26.1	< 0.001

HbA1c, glycated hemoglobin.

Association between TIR and sarcopenia

In our study, the prevalence of sarcopenia was 32.3%. The incidence of sarcopenia in the Q1, Q2, and Q3 groups was 37 cases (43%), 28 cases (38.4%), and 35 cases (23.2%), respectively. Table 2 shows the results of the logistic regression model for sarcopenia with TIR as both a continuous and categorical variable. Overall, TIR exhibited a negative correlation with sarcopenia. When treating TIR as a continuous variable (per 10%), the OR and 95%CI for sarcopenia were 0.85 (0.77–0.93) and 0.83 (0.74–0.93) in model 1 and model 2, respectively, both P = 0.001. When TIR was treated as a categorical variable with Q1 as the reference group, the OR and 95%CI for Q2 and Q3 in model 1 were 0.82 (0.44–1.56), P = 0.551, and 0.4 (0.23–0.71), P = 0.002, respectively. In model 2, the corresponding values were 0.81 (0.38–1.72), P = 0.581 and 0.38 (0.19–0.74), P = 0.005. In model 1 and model 2, the OR and 95%CI for trend tests were 0.63 (0.47–0.83) and 0.6 (0.43–0.84), respectively, both with P < 0.01. The RCS model revealed no evidence of a nonlinear relationship (nonlinearity P value = 0.823) (Fig. 1A).

Table 2.

Association between TIR and Sarcopenia.

	Cases (%)	Model 1		Model 2
		OR (95% CI)	P-value	OR (95% CI)	P-value
Continuous Variable (per 10%)	100 (32.3)	0.85 (0.77 ~ 0.93)	0.001	0.83 (0.74 ~ 0.93)	0.001
Categorical variable
Q1 (< 50%)	37 (43)	1(Ref)		1(Ref)
Q2 (50% ~ 69%)	28 (38.4)	0.82 (0.44 ~ 1.56)	0.551	0.81 (0.38 ~ 1.72)	0.581
Q3 (≥ 70%)	35 (23.2)	0.4 (0.23 ~ 0.71)	0.002	0.38 (0.19 ~ 0.74)	0.005
Trend.test	100 (32.3)	0.63 (0.47 ~ 0.83)	0.001	0.6 (0.43 ~ 0.84)	0.003

Model 1: unadjusted.

Model 2: adjusted for gender, age, marital, smoking status, alcohol consumption, coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, malnutrition, albumin, triglycerides, total cholesterol, and body mass index.

Abbreviations: TIR, time in range. OR, odds ratio; CI, confidence interval.

Fig. 1.

Restricted cubic spline model of time in range with sarcopenia and its components. TIR showed a linear negative correlation with sarcopenia (A) and a linear positive correlation with SMI (B). TIR was non-linearly associated with handgrip strength (C), with an inflection point near 59% (D). TIR showed no significant association with the 5-time chair stand test or gait speed (E). Adjusted: gender, age, marital, smoking status, alcohol consumption, coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, malnutrition, albumin, triglycerides, total cholesterol, and body mass index.

Associations between TIR and components of sarcopenia

Supplementary Tables S1-S4 show the results of linear regression models examining the relationship between TIR and SMI, handgrip strength, 5-time chair stand test, and gait speed, respectively. Model 1 indicated that TIR was positively correlated with SMI, with a β and 95%CI of 0.04 (0–0.08), P = 0.035. TIR was not associated with handgrip strength, the 5-time chair stand test, or gait speed. In model 2, TIR showed positive correlations with both SMI and handgrip strength, with βs and 95%CIs of 0.07 (0.04–0.11) and 0.41 (0.11–0.71), respectively, both P < 0.01. TIR was not significantly associated with 5-time chair stand test and gait speed. Figures 1B-E show the RCS models of TIR and sarcopenia components after adjusting for all covariates. TIR showed a linear positive correlation with SMI (Fig. 1B). TIR showed a non-linear relationship with handgrip strength, with an inflection point near 59% (non-linear P = 0.014) (Fig. 1C). Table 3 shows the inflection point analysis results. TIR showed no significant correlation with either the 5-time chair stand test or gait speed (Fig. 1D and Fig. 1E).

Table 3.

Results of inflection point analysis of handgrip strength.

	Handgrip strength
	Inflection point. β (95%CI)	P-value
Time in Range	59
slope1	-0.012 (-0.084 ~ 0.059)	0.731
slope2	0.196 (0.111 ~ 0.282)	< 0.001
Likelihood Ratio test		< 0.001
Non-linear Test		0.014

Adjusted: gender, age, marital, smoking status, alcohol consumption, coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, malnutrition, albumin, triglycerides, total cholesterol, and body mass index.

Subgroup analysis

Figure 2 presents the results of subgroup analyses after adjusting for all covariates. The association between TIR and sarcopenia remained consistent across subgroups defined by age, gender, coronary heart disease, chronic kidney disease, malnutrition, and BMI, with all interaction P > 0.05.

Fig. 2.

Subgroup Logistic Regression Forest Plot of the Association Between Time in Range (per 10%) and Sarcopenia. Adjusted: gender, age, marital, smoking status, alcohol consumption, coronary heart disease, chronic obstructive pulmonary disease, chronic kidney disease, malnutrition, albumin, triglycerides, total cholesterol, and body mass index.

Discussion

In this cross-sectional study, we investigated the association between TIR with sarcopenia and all four of its components in older diabetic patients, further employing RCS models to explore nonlinear relationships. We found a linear negative relationship between TIR and sarcopenia, with a 17% reduction in sarcopenia incidence per 10% increase in TIR (P < 0.01). After adjusting for all covariates, the incidence of sarcopenia was 62% lower in the TIR ≥ 70% group compared to the TIR < 50% group. Additionally, TIR showed a linear positive relationship with SMI, a nonlinear relationship with grip strength (inflection point: 59%), and no significant association with the 5-time chair stand test or gait speed. Subgroup analyses confirmed that the association between TIR and sarcopenia did not differ significantly across subgroups defined by age, gender, coronary heart disease, chronic kidney disease, malnutrition, or BMI levels.

The prevalence of sarcopenia in our study was 32.3%, which is comparable to the findings reported by Yu et al.²⁵ and Zou et al.²⁶, indicating a prevalence of sarcopenia ranging from 30.06% to 42.2% among hospitalized patients with type 2 diabetes. Our study further confirms that the prevalence of sarcopenia among hospitalized older diabetic patients is generally higher than that observed in the community population^27,28. In a study by Ma et al.²³ also investigating the correlation between TIR and sarcopenia in older diabetic inpatients, the prevalence of sarcopenia was 15.36%, lower than that observed in our study. The reason for the difference in prevalence may be that the mean age of our study population was 76.6 ± 8.8 years, which is higher than the 60–73 years observed in the study by Ma et al., and age is a major risk factor for sarcopenia^26,29.

Previous studies have found that poorer glycaemic control and significant fluctuations are associated with low muscle mass^30,31, which is consistent with our findings. Choe et al. found that poorer glycaemic control was associated with lower handgrip strength among Korean people with type 2 diabetes, with this association being more pronounced in males³². Furthermore, studies on older adults in China have found that hyperglycemia is associated with reduced handgrip strength³³. Unlike our study, the aforementioned research use HbA1c to assess both glycemic control levels. HbA1c, as the gold standard for long-term glycemic control, fails to reveal fluctuations in blood glucose levels, lacking information on glycemic variability or hypoglycemic risk. TIR has been reported to better represent overall glycemic control than HbA1c, directly capturing daily blood glucose variations^18,20. The study by Ma et al.²³ found a negative correlation between TIR and sarcopenia, consistent with our findings. However, in their analysis, Ma et al. did not include TIR as a categorical variable in the model, nor did they assess the dose–response relationship between TIR and the various components of sarcopenia.

Our study observed that higher TIR was associated with higher SMI and handgrip strength, but was not associated with measures of physical function. Based on the existing literature, these associations are biologically plausible. Previous studies have shown that chronic hyperglycemia and glycemic fluctuations may lead to muscle mass loss by increasing advanced glycation end products (AGEs) and activating the ubiquitin–proteasome system ^34,35. Hyperglycemia-induced inflammatory pathways (e.g., NF-κB, TNF-α, IL-6) may lead to mitochondrial dysfunction and reduced muscle strength^35,36. However, because this study employed a cross-sectional design, causal relationships cannot be established, and the aforementioned mechanisms are presented only as speculative hypotheses. Additionally, the nonlinear relationship between TIR and handgrip strength is an exploratory finding that requires further research data for confirmation.

This study comprehensively examined the association between TIR and sarcopenia, muscle mass, muscle strength, and physical function in older adults with T2DM. We found that TIR primarily influences the incidence of sarcopenia through its association with SMI and handgrip strength. These findings suggest that maintaining TIR above a certain threshold may be particularly crucial for preserving muscle mass and strength. However, this study also has some limitations. Firstly, this study is cross-sectional in that it cannot establish a causal relationship between TIR and sarcopenia. Secondly, this study population consisted of hospitalized patients, and the applicability of these findings to the community population requires further research to confirm. Thirdly, the duration of CGM monitoring in this study was only 3 days, which may not be sufficient to reflect the true level of patients’ daily glycemic control. Using CGM for a longer duration in future studies will help address this limitation. In summary, this study provides new evidence for identifying sarcopenia risk in older patients with T2DM. Future prospective cohort studies and interventional trials are warranted to further validate the impact of TIR on sarcopenia and its components.

Conclusion

Higher TIR is associated with higher muscle mass and handgrip strength, as well as a lower incidence of sarcopenia. For older adults with type 2 diabetes who have a low TIR, caution should be exercised regarding their elevated risk of developing sarcopenia.

Author contributions

Conception and design of the study: Zhiping Duan, Hong Yang and Wei Chen. Data collection and processing: Zhiping Duan, Yu Gao, and Qin Hu. Statistical analyses: Zhiping Duan, Yu Gao, and Qin Hu. Writing of the original manuscript: Zhiping Duan, Yu Gao, Qin Hu, and Guihua Jiang. Revision of the manuscript: Hong Yang, Wei Chen, and Yunda Huang. All authors read and approved the final manuscript.

Funding

This work was supported by Scientific Research Fund of Yunnan Provincial Department of Education (grant number: 2024J0866), Third People’s Hospital of Yunnan Province (grant number: 2024SSYKT01, 2024SSYKT03, 2024SSYKT04). The funders had no role in the design, conduct, collection, management, analysis or interpretation of the data, nor in the drafting, review, approval of the manuscript or decision to publish this study.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

All participants received and signed informed consent forms, and the study was approved by the Third People’s Hospital of Yunnan Province ethics committee (2023KY103).