Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study

doi:10.21203/rs.3.rs-3747556/v1

Background

The presence of sarcopenia is significantly correlated with type 2 diabetes mellitus (T2DM). Persistent hyperglycemia and fluctuations in blood glucose levels can have an impact on the muscle mass. So far, no research has assessed potential gender disparities in the relationship between glycated hemoglobin (HbA1c) levels and muscle mass. Therefore, we set out to explore the association between HbA1c levels and muscle mass among T2DM patients.

Methods

This was a cross-sectional study involving 267 elderly hospitalized T2DM patients who were examined by dual-energy X-rays to obtain their muscle mass. They were divided by gender into male and female groups as well as by the appendicular skeletal muscle mass index into "normal muscle mass" or "low muscle mass".

Results

There was a linear correlation between HbA1c and muscle mass in men. HbA1c was significantly associated with low muscle mass, even after adjusted for age, BMI, nephropathy, retinopathy, peripheral neuropathy, hypertension, fasting glucose level, FT3, and TyG index (OR: 1.511 [95%CI: 1.052–2.171], p = 0.026). When HbA1c levels were further disaggregated, multiple regression analyses showed adverse effects on muscle mass when HbA1c was > 7% in men (7%< HbA1c < 8%, OR = 5.78 [95%CI: 1.024–32.596], p = 0.047; HbA1c > 8%, OR = 9.45 [95%CI: 1.978–45.105], p = 0.005). However, no association between HbA1c and muscle mass was observed among females.

Conclusion

High HbA1c levels were linked with low muscle mass in older men with T2DM, but not among women. It is imperative to achieve optimal glycemic control in clinical practice to mitigate the potential of low muscle mass, especially among older men with T2DM.

Old people

Gender differences

Muscle mass

Glycemic control

Sarcopenia is defined as an age-related loss of skeletal muscle mass, diminished muscle strength, and reduced somatic function. It is commonly present among the elderly population. According to Japanese researchers, skeletomuscular-related diseases account for 7.2% of the national burden of disease in old age^[1]. Although there is no standardized diagnosis of sarcopenia, muscle mass plays a key role in its definition. Based on the 2019 Asian Working Group on Sarcopenia (AWGS), a diagnosis of sarcopenia must be made based on the premise of "low muscle mass"^[2].

Type 2 diabetes mellitus (T2DM) has become the 9th leading global cause of mortality^[3]. The global prevalence of T2DM continues to rise in recent years, especially among populations in low- and middle-income countries (LMICs) in the Middle East, North Africa, East Asia, and the South Asia Pacific region. Sarcopenia has been recognized as an emerging complication among patients with DM. Similar to other chronic complications of DM, sarcopenia can adversely affect the patient's prognosis^[4]. Some researchers have also suggested a bidirectional relationship, in which sarcopenia can be both a cause and a consequence of DM^[5]. Previous reports have hypothesized that fluctuating blood glucose levels can be associated with a loss of muscle mass among DM patients when compared with non-diabetic controls. Furthermore, this phenomenon is more pronounced in men, likely attributed to differences in hormone levels and lifestyles between men and women ^{[6, 7]}.

Glycated hemoglobin (HbA1c) as a simple and easily available serological indicator for the assessment of glycemic control in diabetic patients in the past two to three months. Both the American Diabetes Association (ADA)^[8] and the latest Chinese guidelines for the prevention and treatment of T2DM^[9] have included glycosylated hemoglobin as one of the key diagnostic criteria for DM. As glycemic control improves as indicated by a fall in the glycated hemoglobin level, the patient's skeletal muscle mass index will improve^[10].

To the best of our knowledge, most of the published research on diabetes and sarcopenia was conducted among community-based populations even though the prevalence of sarcopenia in hospitalized patients is often higher ^[11]. Therefore, we aimed to conduct a cross-sectional study to elucidate the effects of glycated hemoglobin levels on muscle mass among hospitalized elderly T2DM patients.

Study design and participants

This study was a cross-sectional study and approved by the Ethics Committee of Jiangxi Provincial People's Hospital (No. 2023-29). Due to the anonymous use of data for the purpose of the study, the Ethics Committee of Jiangxi Provincial People's Hospital approved consent for each patient to waive informed consent. All procedures were in accordance with the World Medical Association Declaration of Helsinki^[12].

A total of 267 elderly patients (109 males and 158 females) with T2DM who were hospitalized in Jiangxi Provincial People's Hospital from January 2020 to June 2023 were recruited for this study ( Fig. 1). Ethical approval was obtained from the Ethics Committee of the Jiangxi Provincial People's Hospital. Patient who fulfilled the criteria below were included in the study: (1) Age ≥ 60 years; (2) Previously diagnosed or newly diagnosed T2DM; (3) Patients with a completed whole-body body composition analysis. However, the patients with the following conditions were excluded: (1) severe hepatic insufficiency, moderate to severe renal insufficiency; (2) serious health conditions such as malignant tumors (including malignant tumors of the respiratory, digestive, nervous, hematological, skeletal, connective and other tissues, etc.), acute cerebral infarcts, serious infections, and physical dysfunction; (3) metabolic disorders (hyperthyroidism, hypothyroidism, parathyroid disorders), leukemias, diseases of rheumatoid and immune systems; (4) pregnancy.

The TyG index was used to measure insulin resistance to adjust for potential confounders. It was calculated using triglyceride versus fasting glucose levels (Ln [Fasting triglycerides(mg/dL)x Fasting glucose༈mg/dL༉/2]). This method is easy to perform and commonly used as a proxy indicator of insulin resistance^[13].

DIAGNOSTIC CRITERIA

T2DM

T2DM diagnosis is based on the WHO guidelines^[14], i.e. fasting blood sugar (FBG) ≥ 7.0 mmol/L or random glucose ≥ 11.1 mmol/L after two hours of Oral Glucose Tolerance Test (OGTT) or if one of the following conditions is met: (1) self-reported history of T2DM; (2) taking oral hypoglycemic drugs.

Low muscle mass

According to the recommendations of the Asian Sarcopenia Working Group Report 2019^[2], the appendicular skeletal muscle mass index (ASMI) is calculated by dividing the sum of skeletal muscle mass of both upper and lower limbs by the square of height. Low muscle mass is defined as ASMI of < 7 kg/m2 for men and < 5.4 kg/m2 for women.

Data collection

Patient data were extracted from the medical records in the hospital digital management system, namely age, gender, height, weight, systolic and diastolic blood pressure on admission. history of hypertension, as well as history of diabetic microvascular complications (nephropathy, peripheral neuropathy, and retinopathy) were based on information provided by the patient's medical history or detected on examination at the time of this hospitalisation. Serological parameters obtained from all patients after eight hours of fasting included alanine aminotransferase, aspartate aminotransferase, triglycerides, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, creatinine, glucose, thyrotropin, free triiodothyronine thyroxine and free thyroxine,etc. Finally, muscle mass was assessed using dual-energy X-rays.

Statistical Analysis

Statistical analysis was conducted using SPSS version 26.0. Normally-distributed data were expressed as mean ± standard deviation and compared using a t-test while data that were not normally distributed were transformed to normal distribution. Categorical variables were expressed as the number and percentage [n (%)] and compared using Chi-square(χ²). Spearman's correlation analysis was used to test the correlation between ASMI with the patient’s age, body mass index (BMI), and serological profiles. Logistic regression was performed to investigate whether glycated hemoglobin was an independent risk factor for ASMI.

After that, the patients were divided into four groups based on the glycated hemoglobin levels (Group 1: < 6.5%, Group 2: 6.5%-6.9%, Group 3: 7.0%-7.9%, Group 4: ≥ 8.0%). Group 1 was used as a reference to investigate the effects of different glycated hemoglobin levels on the muscle mass index of the patients and to compare the differences in muscle mass between the groups. P < 0.05 was considered statistically significant.

Table 1 outlines the baseline characteristics of all patients. There was a higher prevalence of low muscle mass in men with T2DM compared to women. In terms of diabetic complications, male patients with low muscle mass were associated with a higher prevalence of underlying comorbid diabetic peripheral neuropathy, higher levels of fasting glucose, glycated hemoglobin, and lower hemoglobin levels than their counterparts with normal muscle mass. Among female DM patients with low muscle mass, they reported lower levels of total albumin, albumin, uric acid, and serum phosphorus ions. For both male and female patients, those in the reduced muscle mass group were older and had lower BMI and FT3 levels compared to patients with normal muscle mass. Table 2 highlights that glycosylated hemoglobin levels became higher when muscle mass decreased in male patients. A similar trend was observed among female patients, but it was not statistically significant (Male: r= -0.328, p< 0.001; female: r= -0.110, p=0.169).

To further elucidate whether the relationship between glycated hemoglobin and low muscle mass in T2DM patients was independent of other covariates, logistic regression analyses were performed separately. Three models were developed (Model 1: adjusted for patient's age and BMI; Model 2: adjusted for diabetic nephropathy, diabetic retinopathy, diabetic peripheral neuropathy, and hypertension based on Model 1; and Model 3: Adjustment for FT3, fasting glucose, and TyG index based on Model 2. From the results, glycosylated hemoglobin was strongly associated with low muscle mass in men. The relationship remained significant even after adjusting for general characteristics, microvascular complications of diabetes, hypertension, and potential serological indicators. However, no association between glycated hemoglobin and muscle mass was observed among female patients after adjusting for all covariates (Table 3).

In addition, the patients were split into four groups based on their glycated hemoglobin levels. A two-by-two comparison of ASMI levels was performed between the groups. ASMI was only lower in the male group when HbA1c was equal to or greater than 8.0%, as compared to those with HbA1c less than 6.5% (P= 0.006) and 6.5% ≤ HbA1c <7.0% (P= 0.046) (Figure 2a). In the female group, no differences in ASMI were detected between groups with different levels of glycated hemoglobin (Figure 2b). Multivariate logistic regression analyses were conducted to investigate whether different glycated hemoglobin levels had an independent effect on muscle mass while adjusting for potential confounders. Normal glycated hemoglobin level (HbA1c< 6.5%) was used as the reference. The risk of low muscle mass was higher in the male group in the male group of 7.0% < HbA1c < 8.0% (OR: 5.78 [95% CI: 1.024-32.596], p= 0.047) and HbA1c > 8.0% (OR: 9.45 [95% CI: 1.978-45.105], p= 0.005) compared to the reference group. However, in the female group, there was no statistically significant difference between the normal and elevated HbA1c groups (Table 4).

Loss of muscle mass is a prerequisite for the diagnosis of sarcopenia. DM has been linked with an increasing risk of sarcopenia. However, most studies have been conducted on diabetic versus non-diabetic controls in the general population. The majority of study participants were hospitalized in the endocrinology department because of poor glycemic control. Even though some of them had comorbidities and other diseases, we excluded hospitalized patients with other disease comorbidities to minimize the potential impact of these diseases on muscle mass.

The present study demonstrated the adverse effects cast by elevated glycated hemoglobin levels on muscle mass, as well as the gender disparity. The association between muscle mass loss and elevated glycated hemoglobin was more pronounced among male patients, even after adjusting for age, BMI, diabetic comorbidities, hypertension, TyG index, and serological markers. In both between-group and stratified analyses, the risk of "low muscle mass" was increased for HbA1c ≤ 7%. In addition, not only was the risk of "low muscle mass" increased for HbA1c ≥ 8.0% but there was also a significantly lower muscle mass in this cohort compared with male patients with HbA1c < 6.5% and 6.5%≤ HbA1c < 7.0%. However, a similar phenomenon was not observed in women.

Previous studies have shown that elevated HbA1c in diabetic patients may be linearly associated with the development of sarcopenia, in which chronically hyperglycemic patients were predisposed to reduced muscle mass compared to those with normal HbA1c < 6.5%^[15]. A longitudinal cohort study followed 588 patients with T2DM for one year and found that patients with a reduction in HbA1c levels of more than one percent restored their muscle mass during the follow-up period^[10]. It can be hypothesized that high levels of HbA1c negatively affect muscle mass. However, their hyperglycemic state appeared to normalize after a certain period when the patient's muscle mass improved, thus suggesting a potential bi-directional relationship between DM and sarcopenia. Although the detailed mechanism of this relationship has not been fully elucidated, skeletal muscle could likely have increase blood glucose levels as its mass decreases as it is one of the target organs for material conversion and energy metabolism in response to glucose^{[16, 17]}. Suboptimal blood glucose control can render our body in a state of "glycation", subsequently causing an accumulation of advanced glycosylation end products (AGEs). Proteins that are present in the extracellular matrix of human skeletal muscles are highly susceptible to chemical modification. For instance, the reduction of glyoxal groups to form AGEs can cause extensive damage to the corresponding tissues and exacerbate the negative effects on skeletal muscle mass through an up-regulation of inflammatory responses^{[18, 19]}.

On the other hand, insulin resistance has also been postulated as the link of the relationship between sarcopenia and DM. Insulin, the only hypoglycemic hormone secreted synthetically by the human body, occurs as a direct result of disruption in normal blood glucose levels^[20]. In addition, insulin induces the synthesis of several proteins via the IGF1-Akt-FoxO pathway, resulting in skeletal muscle hypertrophy and inhibition of protein degradation in skeletal muscle cells. Subsequently, the down-regulation of this molecular pathway in insulin-resistant cells may lead to muscle wasting^{[21, 22]}.

Glycated hemoglobin levels in this study were considered high for both men (8.00 ± 2.02) and women (7.77 ± 1.78). Therefore, its effect on muscle mass appeared to be more pronounced. Age and BMI of diabetic patients had been established as potential risk factors of sarcopenia^[23], consistent with our findings (Supplementary Table 1, Supplementary Table 2). With regard to gender disparity in the effect of blood glucose levels on the muscle mass of diabetic patients, several studies reported similar findings as our research. Xiulin Shi et al. recruited 1084 participants and reported an association between low muscle mass and higher blood glucose fluctuations in male patients, even if they were on the same insulin regime^[6]. In another study conducted in Korea, HbA1c ≥ 8.5% was a risk factor for low muscle mass in men^[24]. However, the definition of low muscle mass in this study was limited to the lowest quartile of the sample rather than following the recommended guidelines. The study also did not include female patient controls, thus compromising the generalizability of the study results and comparability with other studies.

As far as we are concerned, our study is one of the first that reported gender differences in the effect of HbA1c on muscle mass. Separate analyses of male and female patients hospitalized during the same period revealed a linear relationship between HbA1c and muscle mass in males. Furthermore, HbA1c levels of more than 7% could be a risk factor for low muscle mass. Despite the unclear mechanism underlying the gender difference, we postulated that it could be influenced by certain underlying factors and biological mechanisms. To begin with, the prevalence of diabetes is higher in men than in women due to lifestyles, behaviors, and other risk factors^[25]. Biologically, women are protected against insulin resistance triggered by non-esterified fatty acids (NEFA)^[26] and therefore show a greater capacity to combat lipotoxicity in skeletal muscle than men^[27]. In addition, sex hormones play different roles in regulating skeletal muscle homeostasis. For males, testosterone promotes protein synthesis, muscle regeneration, and maintenance of muscle mass. Older men with declining testosterone levels are at an increased risk of sarcopenia^[28]. In contrast, estrogens in females may protect skeletal muscles by reducing inflammatory responses^[29].

There are certain limitations and strengths to this study. One of the strengths is that the effects of thyroid function on muscles were taken into account. Previous research on the association between thyroid hormones and muscle mass in T2DM patients showed that FT3 levels were protective against loss of muscle mass^{[30, 31]}. To better assess the association between HbA1c and muscle mass, we further adjusted for FT3. After adjusting for these associations, the association was still highly significant in men. In terms of study limitations, the cross-sectional design means that a causal relationship cannot be established between HbA1c levels and muscle mass. Therefore, future prospective studies are needed to validate the results. Secondly, although diabetes complications were accounted for, we did not assess the glucose-lowering medications used and the duration of diabetes among the patients. Some medications (e.g. insulin, metformin) may affect muscle growth. For example, a multicenter study of older men with diabetes showed reduced muscle loss among those taking metformin compared to those not taking it^{[32, 33]}. As these medications are commonly prescribed for T2DM patients, their effects on muscle mass should be further investigated. Thirdly, our results suggested that high HbA1c in men might predispose to low muscle mass. However, this result should be interpreted with caution due to the small sample size, especially with the low number of female patients with low muscle mass. Further expansion of the sample size is needed to better elucidate gender differences between high HbA1c and low muscle mass. Despite these limitations, our research provides new strategies and recommendations for reducing the risk of muscle mass loss among older T2DM hospitalized patients.

In summary, this study examined gender differences in the relationship between HbA1c levels and muscle mass among hospitalized T2DM patients. Age was a significant risk factor for the loss of muscle mass in both men and women while BMI played a protective role. Furthermore, higher HbA1c levels were significantly associated with low muscle mass in older men with T2DM even after adjusting for numerous confounders unlike in women. In other words, high blood glucose levels exert a more pronounced negative impact on muscle mass in older men with T2DM. Thus, optimal glycemic control should be the ultimate aim of clinical practice, especially among male T2DM patients with low muscle mass.

T2DM

type 2 diabetes mellitus

HbA1c

glycated hemoglobin

BMI

Body Mass Index

FT3

free triiodothyronine

AWGS

Asian Working Group on Sarcopenia

LMICs

low- and middle-income countries

ADA

American Diabetes Association

FPG

fasting blood sugar

OGTT

Oral Glucose Tolerance Test

ASMI

appendicular skeletal muscle mass index

OR

Odds Ratio

CI

Confidence Interval

AGEs

advanced glycosylation end products

NEFA

non-esterified fatty acids

IGF-1

insulin-like growth factor 1

Akt

protein kinase B

FoxO

Forkhead transcription factor.

Ethics approval and consent to participate

This study was a retrospective cross-sectional study and approved by the Ethics Committee of Jiangxi Provincial People's Hospital (No. 2023-29). Due to the anonymous use of data for the purpose of the study, the Ethics Committee of Jiangxi Provincial People's Hospital approved consent for each patient to waive informed consent. All procedures were in accordance with the World Medical Association Declaration of Helsinki.

Consent for publication

Not applicable.

Availability of data and meterials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interest.

Funding

No specific funding for this research has been announced by any funding agency in the public, commercial, or nonprofit sectors.

Authors’ contribution

JH, JTW and FXCconceived and designed the study idea. JH, JTW, and MQ performed data extraction and statistical analysis. JTW drafted the article, and JH conducted a critical review of the intellectual content of the article.All authors contributed to the writing and editing of the manuscript and agreed to the final manuscript.

Acknowledgements

Not applicable.

Authors’ information

¹ Jiangxi Medical College, Nanchang University;

² Jiangxi Provincial People's Hospital，The First Affiliated Hospital of Nanchang Medical College.

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Table 1.Characteristics of T2DM participants in the low and non-low muscle mass groups stratified by sex.

	male			female
	Non- Low muscle mass	Low muscle mass	P value	Non- Low muscle mass	Low muscle mass	P value
N	49	60		121	37
Age (years)	67.31±7.30	72.30±9.25	0.002	72.03±7.89	75.35±8.33	0.029
BMI (kg/m²)	25.02±3.10	22.41±2.41	0.001	25.32±4.53	21.76±3.48	0.001
Diastolic BP（mmHg）	80.24±8.69	78.47±10.45	0.434	77.92±10.77	71.89±11.12	0.002
Systolic BP（mmHg）	132.57±13.15	134.85±19.19	0.466	138.79±19.33	137.86±22.38	0.808
Diabetic nephropathy n (%)	11（22.45）	18（30）	0.375	14（11.57）	6（14.63）	0.549
Diabetic retinopathy n (%)	13（26.53）	9（15）	0.136	12（9.91）	7（17.07）	0.305
Diabetic peripheral neuropathy n (%)	21（42.85）	38（63.33）	0.033	48（39.66）	15（36.58）	0.853
Hypertension n (%)	38（77.55）	43（71.37）	0.484	85（70.24）	24（58.53）	0.184
Total protein (g/L)	66.93±6.30	66.16±5.76	0.511	67.51±5.38	65.45±4.06	0.015
Albumin (g/L)	39.01±3.61	37.57±4.05	0.056	38.91±4.22	36.54±3.57	0.002
Creatinine (umol/L)	75.56±15.49	84.98±33.09	0.209	59.36±17.21	60.59±21.22	0.926
UA (umol/L)	357.69±83.32	355.03±99.55	0.882	319.53±91.44	289.59±89.16	0.036
ALT (U/L)	20.87±10.57	17.90±8.61	0.052	16.95±7.72	18.00±8.54	0.871
AST (U/L)	19.73±6.33	19.51±5.38	0.855	19.17±5.59	19.59±7.08	0.909
HDL cholesterol (mmol/L)	1.14±0.39	1.13±0.40	0.781	1.25±0.32	1.30±0.50	0.82
LDL cholesterol (mmol/L)	2.52±0.91	2.44±0.87	0.672	2.70±0.89	2.57±0.94	0.347
Ca (mmol/L)	2.26±0.07	2.24±0.11	0.41	2.27±0.11	2.26±0.13	0.424
FBG (mmol/L)	6.52±1.45	8.63±4.02	0.001	7.59±2.97	9.07±4.84	0.132
HbA1c (％)	7.21±1.49	8.64±2.17	＜0.001	7.62±1.67	8.23±2.05	0.112
Hemoglobin (g/L)	140.59±15.85	131.48±20.14	0.011	125.08±10.93	119.68±17.67	0.085
Platelet (10^9/L)	189.69±53.02	195.67±55.79	0.52	211.63±58.64	202.95±68.38	0.450
Neutrophil count (10^9/L)	4.05±1.42	3.90±1.42	0.655	3.64±1.29	3.95±1.39	0.215
Triglycerides (mmol/L)	1.47±0.85	1.52±1.01	0.947	1.69±0.94	1.88±1.18	0.33
Total cholesterol (mmol/L)	4.10±0.96	4.00±0.92	0.588	4.51±1.11	4.45±0.95	0.89
TSH (ulU/L)	2.39±1.34	2.48±1.67	0.836	2.69±1.45	2.70±2.20	0.245
FT3 (ulU/L)	4.58±0.63	4.20±0.79	0.007	4.30±0.62	3.91±0.54	0.001
FT4 (ulU/L)	16.99±2.28	17.08±2.38	0.830	16.88±2.02	16.25±1.98	0.088
TyG Index	8.79±0.58	8.99±0.74	0.125	9.07±0.69	9.28±0.76	0.111

BMI, body mass index；UA，uric acid；ALT，alanine aminotransferase；AST，aspartate aminotransferase；Ca，calcium；FBG，fasting blood sugar；HbA1c，glycosylated hemoglobin;TSH ,thyrotropin; FT3 , free triiodothyronine;FT4 , free thyroxine;TyG Index,Triglyceride-Glucose Index.Values are mean (SD), or median [IQR] for continuous variables, and N (%) for categorical variables.Statistical significance was assessed by paired t-test or chi-square test.

Table 2.Correlation analysis of each parameter with ASMI.

	male		female
	r	P	r	P
HbA1c (％)	﹣0.328	＜0.001	﹣0.110	0.169
Age (years)	﹣0.330	＜0.001	﹣0.203	0.011
BMI (kg/m2)	0.607	＜0.001	0.665	＜0.001
Albumin (g/L)	0.279	0.003	0.119	0.138
Triglycerides (mmol/L)	0.013	0.891	0.057	0.48
Totalcholesterol(mmol/L)	0.081	0.404	﹣0.046	0.568
HDL (mmol/L)	﹣0.020	0.834	﹣0.123	0.125
LDL (mmol/L)	0.043	0.659	0.036	0.651
FBG (mmol/L)	﹣0.234	0.014	﹣0.091	0.256
Hemoglobin (g/L)	0.406	＜0.001	0.168	0.035
TSH (ulU/L)	0.007	0.941	0.139	0.082
FT3 (ulU/L)	0.381	＜0.001	0.274	＜0.001
FT4 (ulU/L)	﹣0.099	0.306	0.074	0.354

Correlations were analyzed using the Spearman correlation coefficient.

Table 3.The association between ASMI and glycosylated hemoglobin was derived by Logistic Regression Models.

		HbA1c
	SMI	Model 1		Model 2		Model 3
	SMI	Odds ratio（95％CI）	P	Odds ratio（95％CI）	P	Odds ratio（95％CI）	P
male	Non- Low muscle mass	ref.		ref.		ref.
male	Low muscle mass	1.677（1.219-2.307）	0.001	1.576（1.134-2.191）	0.007	1.511（1.052-2.171）	0.026
female	Non- Low muscle mass	ref.		ref.		ref.
female	Low muscle mass	1.202（0.974-1.482）	0.086	1.155（0.923-1.444）	0.207	1.053(0.792-1.401)	0.722

Model 1: adjusted for Age, BMI, and HbA1c .

Model 2:adjusted for covariates in Model 1 plus Diabetic nephropathy ,Diabetic retinopathy ,Diabetic peripheral neuropathy ,Hypertension .

Model 3: adjusted for covariates in Model 2 plus FBG,FT3,TyG Index.

BMI, body mass index;HbA1c,glycosylated hemoglobin;FBG，fasting blood sugar；FT3 , free triiodothyronine;TyG Index,Triglyceride-Glucose Index.

Table 4.Multivariate Regression analysis of the risk of muscle mass loss associated with glycemic control.

		male			female
		Odds ratio（95％CI）	P		Odds ratio（95％CI）	P
HbA1c
＜6.5	ref	1.000		ref	1.000
6.5-6.9		3.919（0.772-19.885）	0.099		1.185(0.279-5.043)	0.818
7.0-7.9		5.777（1.024-32.596）	0.047		1.015(0.261-3.948)	0.983
≥8.0		9.446（1.978-45.105）	0.005		1.699(0.443-6.512)	0.439

Multivariate analysis of the association between different glycated hemoglobin levels and SMI in Model 3.ref.reference

No competing interests reported.

Supplementarytable.docx

Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study

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Abstract

Background

Methods

Results

Conclusion

Figures

INTRODUCTION

METHODOLOGY

Study design and participants

DIAGNOSTIC CRITERIA

T2DM

Low muscle mass

Data collection

Statistical Analysis

RESULTS

DISCUSSION

CONCLUSION AND IMPLICATIONS

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

References

Tables

Additional Declarations

Supplementary Files

Status:

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