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

Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study Wang jintao, Jian Hu, Faxiu Chen, Tianjin Huang, Chen Li, Yuting Chen, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3747556/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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 = 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 Figures Figure 1 Figure 2 INTRODUCTION 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. METHODOLOGY 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( χ 2 ). 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. RESULTS 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: 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). DISCUSSION 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. CONCLUSION AND IMPLICATIONS 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. Abbreviations 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. Declarations 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. 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Tables 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/m 2 ) 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 Odds ratio（95％CI） P Odds ratio（95％CI） P Odds ratio（95％CI） P male Non- Low muscle mass ref. ref. ref. 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. 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 Additional Declarations No competing interests reported. Supplementary Files Supplementarytable.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3747556","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":263690258,"identity":"f2c3a681-17f0-4aec-a3d9-344c39146713","order_by":0,"name":"Wang jintao","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Wang","middleName":"","lastName":"jintao","suffix":""},{"id":263690259,"identity":"8c7581cd-f6e7-4153-8d10-99f4d55edb8e","order_by":1,"name":"Jian Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACAyA+wMPAIMfP3nzgwIcfJGgxluw5lnhwZg+RWhiAWhI33MgxPszBRoQWc4kcwwNvamwSN5w58+EwULM8v9gB/FosZ+QYHJxzLM145vHeDYcLLBgMZ85OIOCwGzkGh3nYDsv2nTm74fAMHoYEg9tEafl3mLHhRs4DoF5itfC2HVaccCOHgUgtZ54VHJzblwYKZANgIEsQ4ZfjyZs/vPlmA4rKxx8+/LCR55cmoIWBgcMAmSdBSDkIsD8gRtUoGAWjYBSMZAAAXctRT3yIIAIAAAAASUVORK5CYII=","orcid":"","institution":"Jiangxi Provincial People's Hospital，The First Affiliated Hospital of Nanchang Medical College","correspondingAuthor":true,"prefix":"","firstName":"Jian","middleName":"","lastName":"Hu","suffix":""},{"id":263690260,"identity":"b287dbfd-3d06-45ba-9fd6-2e03171f60f3","order_by":2,"name":"Faxiu Chen","email":"","orcid":"","institution":"Jiangxi Provincial People's Hospital，The First Affiliated Hospital of Nanchang Medical College","correspondingAuthor":false,"prefix":"","firstName":"Faxiu","middleName":"","lastName":"Chen","suffix":""},{"id":263690261,"identity":"2a54f188-5eb5-4c27-8d61-94fc1d063225","order_by":3,"name":"Tianjin Huang","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Tianjin","middleName":"","lastName":"Huang","suffix":""},{"id":263690262,"identity":"19cb73f4-f98f-4506-b1cd-7ed9d7500938","order_by":4,"name":"Chen Li","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Li","suffix":""},{"id":263690263,"identity":"30a92e4c-6a17-4fa5-962a-e658be3bea0c","order_by":5,"name":"Yuting Chen","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Yuting","middleName":"","lastName":"Chen","suffix":""},{"id":263690264,"identity":"0e53e39c-0554-40ad-8d43-c54e02165c2d","order_by":6,"name":"Jiming Li","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Jiming","middleName":"","lastName":"Li","suffix":""},{"id":263690265,"identity":"f006e9a3-1907-4463-9910-9a4b48e21f9f","order_by":7,"name":"Qian Ma","email":"","orcid":"","institution":"Jiangxi Medical College, Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Ma","suffix":""}],"badges":[],"createdAt":"2023-12-13 09:14:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3747556/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3747556/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49071757,"identity":"b4101e90-50c8-4dfb-beca-ca1f5732c0f7","added_by":"auto","created_at":"2024-01-02 17:13:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22397,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the study population.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3747556/v1/6a43379d44bee79f94eb0720.png"},{"id":49071759,"identity":"7c4ecf10-6351-4713-ad9f-b1f35c05bb75","added_by":"auto","created_at":"2024-01-02 17:13:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":22669,"visible":true,"origin":"","legend":"\u003cp\u003ea. Poor glycemic control was associated with lower SMI in male. Older male T2DM patients with 8 ≤ HbA1c have significantly reduced SMI compared to those with HbA1c\u0026lt;7.\u003csup\u003e*\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e＜0.05，\u003csup\u003e**\u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e=0.006.\u003c/p\u003e\n\u003cp\u003eb.Poor glycemic control in female was not associated with SMI levels.\u003c/p\u003e","description":"","filename":"floatimage232.png","url":"https://assets-eu.researchsquare.com/files/rs-3747556/v1/e1f0c42c0fe9ea101eccb7d2.png"},{"id":49073189,"identity":"b32b5123-2902-4235-89a5-7f4312f1062c","added_by":"auto","created_at":"2024-01-02 17:29:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":367489,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3747556/v1/7912cc6d-4a4e-4446-b43f-04c94f3c3844.pdf"},{"id":49071758,"identity":"e4890a99-6b16-4505-b78b-1d7a7af9ce28","added_by":"auto","created_at":"2024-01-02 17:13:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17299,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-3747556/v1/57e7221fe5c659a742bfb748.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSarcopenia 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\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. 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\"\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eType 2 diabetes mellitus (T2DM) has become the 9th leading global cause of mortality\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Some researchers have also suggested a bidirectional relationship, in which sarcopenia can be both a cause and a consequence of DM\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. 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 \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGlycated 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)\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e and the latest Chinese guidelines for the prevention and treatment of T2DM\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e 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\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo 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 \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. 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.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis 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\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA 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.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). 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\u0026thinsp;\u0026ge;\u0026thinsp;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.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe 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\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDIAGNOSTIC CRITERIA\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eT2DM\u003c/h2\u003e \u003cp\u003eT2DM diagnosis is based on the WHO guidelines\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, i.e. fasting blood sugar (FBG)\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L or random glucose\u0026thinsp;\u0026ge;\u0026thinsp;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.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eLow muscle mass\u003c/h2\u003e \u003cp\u003eAccording to the recommendations of the Asian Sarcopenia Working Group Report 2019\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, 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 \u0026lt;\u0026thinsp;7 kg/m2 for men and \u0026lt;\u0026thinsp;5.4 kg/m2 for women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003ePatient 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.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was conducted using SPSS version 26.0. Normally-distributed data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;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(\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e). Spearman's correlation analysis was used to test the correlation between ASMI with the patient\u0026rsquo;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.\u003c/p\u003e \u003cp\u003eAfter that, the patients were divided into four groups based on the glycated hemoglobin levels (Group 1: \u0026lt; 6.5%, Group 2: 6.5%-6.9%, Group 3: 7.0%-7.9%, Group 4: \u0026ge; 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. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTable 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\u0026lt; 0.001; female: r= -0.110, p=0.169).\u003c/p\u003e\n\u003cp\u003eTo 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\u0026apos;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).\u003c/p\u003e\n\u003cp\u003eIn 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% (\u003cem\u003eP\u003c/em\u003e= 0.006) and 6.5% \u0026le; HbA1c \u0026lt;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\u0026nbsp;(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\u0026lt; 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% \u0026lt; HbA1c \u0026lt; 8.0% (OR: 5.78 [95% CI: 1.024-32.596], \u003cem\u003ep\u003c/em\u003e= 0.047) and HbA1c \u003cu\u003e\u0026gt;\u0026nbsp;\u003c/u\u003e8.0% (OR: 9.45 [95% CI: 1.978-45.105], \u003cem\u003ep\u003c/em\u003e= 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).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eLoss 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.\u003c/p\u003e \u003cp\u003eThe 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 \u0026lt; 6.5% and 6.5%≤ HbA1c \u0026lt; 7.0%. However, a similar phenomenon was not observed in women.\u003c/p\u003e \u003cp\u003ePrevious 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 \u0026lt; 6.5%\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOn 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\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGlycated 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\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e, consistent with our findings (Supplementary Table\u0026nbsp;1, Supplementary Table\u0026nbsp;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\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In another study conducted in Korea, HbA1c ≥ 8.5% was a risk factor for low muscle mass in men\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. 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.\u003c/p\u003e \u003cp\u003eAs 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\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. Biologically, women are protected against insulin resistance triggered by non-esterified fatty acids (NEFA)\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e and therefore show a greater capacity to combat lipotoxicity in skeletal muscle than men\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. In contrast, estrogens in females may protect skeletal muscles by reducing inflammatory responses\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere 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\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. 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\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. 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.\u003c/p\u003e "},{"header":"CONCLUSION AND IMPLICATIONS","content":"\u003cp\u003eIn 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.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2DM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etype 2 diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHbA1c\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eglycated hemoglobin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody Mass Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFT3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efree triiodothyronine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAWGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAsian Working Group on Sarcopenia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLMICs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elow- and middle-income countries\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Diabetes Association\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFPG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efasting blood sugar\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOGTT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOral Glucose Tolerance Test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eappendicular skeletal muscle mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eCI\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAGEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadvanced glycosylation end products\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNEFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-esterified fatty acids\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIGF-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einsulin-like growth factor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAkt\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprotein kinase B\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFoxO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eForkhead transcription factor.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThis study was a retrospective cross-sectional study and approved by the Ethics Committee of Jiangxi Provincial People\u0026apos;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\u0026apos;s Hospital approved consent for each patient to waive informed consent. All procedures were in accordance with the World Medical Association Declaration of Helsinki.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and meterials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding for this research has been announced by any funding agency in the public, commercial, or nonprofit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJH, JTW and FXCconceived and designed the study idea. JH, JTW, and MQ performed data extraction and statistical analysis.\u0026nbsp;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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Jiangxi Medical College, Nanchang University;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Jiangxi Provincial People\u0026apos;s Hospital，The First Affiliated Hospital of Nanchang Medical College.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKitamura A, Seino S, Abe T, Nofuji Y, Yokoyama Y, Amano H, et al. 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Diabet Med. 1998;15(7):539\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSugimoto K, Tabara Y, Ikegami H, Takata Y, Kamide K, Ikezoe T, et al. Hyperglycemia in non-obese patients with type 2 diabetes is associated with low muscle mass: The multicenter study for clarifying evidence for sarcopenia in patients with diabetes mellitus. J Diabetes Investig. 2019;10(6):1471\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalyani RR, Metter EJ, Ramachandran R, Chia CW, Saudek CD, Ferrucci L. Glucose and insulin measurements from the oral glucose tolerance test and relationship to muscle mass. J Gerontol A Biol Sci Med Sci. 2012;67(1):74\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRattarasarn C, Leelawattana R, Soonthornpun S. Contribution of skeletal muscle mass on sex differences in 2-hour plasma glucose levels after oral glucose load in thai subjects with normal glucose tolerance. Metabolism. 2010;59(2):172\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSemba RD, Nicklett EJ, Ferrucci L. Does accumulation of advanced glycation end products contribute to the aging phenotype? J Gerontol A Biol Sci Med Sci. 2010;65(9):963\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTabara Y, Ikezoe T, Yamanaka M, Setoh K, Segawa H, Kawaguchi T, et al. Advanced glycation end product accumulation is associated with low skeletal muscle mass, weak muscle strength, and reduced bone density: The nagahama study. J Gerontol A Biol Sci Med Sci. 2019;74(9):1446\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Y, Ley SH, Hu FB. Global aetiology and epidemiology of type 2 diabetes mellitus and its complications. Nat Rev Endocrinol. 2018;14(2):88\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanerjee A, Apponi LH, Pavlath GK, Corbett AH. Pabpn1: Molecular function and muscle disease. Febs j. 2013;280(17):4230\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBanerjee A, Guttridge DC. Mechanisms for maintaining muscle. Curr Opin Support Palliat Care. 2012;6(4):451\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUmegaki H. Sarcopenia and frailty in older patients with diabetes mellitus. Geriatr Gerontol Int. 2016;16(3):293\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoon JW, Ha YC, Kim KM, Moon JH, Choi SH, Lim S, et al. Hyperglycemia is associated with impaired muscle quality in older men with diabetes: The korean longitudinal study on health and aging. Diabetes Metab J. 2016;40(2):140\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorldwide trends in diabetes since 1980. A pooled analysis of 751 population-based studies with 4.4 million participants. Lancet. 2016;387(10027):1513\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTramunt B, Smati S, Grandgeorge N, Lenfant F, Arnal JF, Montagner A, et al. Sex differences in metabolic regulation and diabetes susceptibility. Diabetologia. 2020;63(3):453\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrias JP, Macaraeg GB, Ofrecio J, Yu JG, Olefsky JM, Kruszynska YT. Decreased susceptibility to fatty acid-induced peripheral tissue insulin resistance in women. Diabetes. 2001;50(6):1344\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson LJ, Liu H, Garcia JM. Sex differences in muscle wasting. Adv Exp Med Biol. 2017;1043:153\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim KM, Jang HC, Lim S. Differences among skeletal muscle mass indices derived from height-, weight-, and body mass index-adjusted models in assessing sarcopenia. Korean J Intern Med. 2016;31(4):643\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen L, Zhang M, Xiang S, Jiang X, Gu H, Sha Q, et al. Association between thyroid function and body composition in type 2 diabetes mellitus (t2dm) patients: Does sex have a role? Med Sci Monit. 2021;27:e927440.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang LN, Zhong S, Ma D, Hao YM, Gao Y, Zhang L, et al. Association between thyroid hormones and skeletal muscle and bone in euthyroid type 2 diabetes patients. Ther Adv Chronic Dis. 2022;13:20406223221107848.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng C, Liu Z. Vascular function, insulin action, and exercise: An intricate interplay. Trends Endocrinol Metab. 2015;26(6):297\u0026ndash;304.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee CG, Boyko EJ, Barrett-Connor E, Miljkovic I, Hoffman AR, Everson-Rose SA, et al. Insulin sensitizers may attenuate lean mass loss in older men with diabetes. Diabetes Care. 2011;34(11):2381\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1.Characteristics of T2DM participants in the low and non-low muscle mass groups stratified by sex.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.387755102040817%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"3\" style=\"width: 37.5657%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.775510204081634%\" colspan=\"3\" style=\"width: 37.5657%;\"\u003e\n \u003cp\u003e\u003cstrong\u003efemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon- Low muscle mass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow muscle mass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon- Low muscle mass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow muscle mass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e67.31\u0026plusmn;7.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e72.30\u0026plusmn;9.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e72.03\u0026plusmn;7.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e75.35\u0026plusmn;8.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e25.02\u0026plusmn;3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e22.41\u0026plusmn;2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e25.32\u0026plusmn;4.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e21.76\u0026plusmn;3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eDiastolic BP（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e80.24\u0026plusmn;8.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e78.47\u0026plusmn;10.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e77.92\u0026plusmn;10.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e71.89\u0026plusmn;11.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eSystolic BP（mmHg）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e132.57\u0026plusmn;13.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e134.85\u0026plusmn;19.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e138.79\u0026plusmn;19.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e137.86\u0026plusmn;22.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eDiabetic nephropathy n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e11（22.45）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e18（30）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e14（11.57）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e6（14.63）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.549\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eDiabetic retinopathy n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e13（26.53）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e9（15）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e12（9.91）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e7（17.07）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.305\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eDiabetic peripheral neuropathy n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e21（42.85）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e38（63.33）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e48（39.66）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e15（36.58）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eHypertension n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e38（77.55）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e43（71.37）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e85（70.24）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e24（58.53）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eTotal protein (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e66.93\u0026plusmn;6.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e66.16\u0026plusmn;5.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e67.51\u0026plusmn;5.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e65.45\u0026plusmn;4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eAlbumin \u0026nbsp;(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e39.01\u0026plusmn;3.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e37.57\u0026plusmn;4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e38.91\u0026plusmn;4.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e36.54\u0026plusmn;3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eCreatinine (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e75.56\u0026plusmn;15.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e84.98\u0026plusmn;33.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e59.36\u0026plusmn;17.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e60.59\u0026plusmn;21.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.926\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eUA (umol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e357.69\u0026plusmn;83.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e355.03\u0026plusmn;99.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e319.53\u0026plusmn;91.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e289.59\u0026plusmn;89.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eALT (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e20.87\u0026plusmn;10.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e17.90\u0026plusmn;8.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e16.95\u0026plusmn;7.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e18.00\u0026plusmn;8.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.871\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eAST (U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e19.73\u0026plusmn;6.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e19.51\u0026plusmn;5.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e19.17\u0026plusmn;5.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e19.59\u0026plusmn;7.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eHDL cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.14\u0026plusmn;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.13\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.25\u0026plusmn;0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.30\u0026plusmn;0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.52\u0026plusmn;0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.44\u0026plusmn;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.70\u0026plusmn;0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.57\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eCa (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.26\u0026plusmn;0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.24\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.27\u0026plusmn;0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.26\u0026plusmn;0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.424\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eFBG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e6.52\u0026plusmn;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e8.63\u0026plusmn;4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e7.59\u0026plusmn;2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e9.07\u0026plusmn;4.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eHbA1c (％)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e7.21\u0026plusmn;1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e8.64\u0026plusmn;2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e7.62\u0026plusmn;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e8.23\u0026plusmn;2.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e140.59\u0026plusmn;15.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e131.48\u0026plusmn;20.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e125.08\u0026plusmn;10.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e119.68\u0026plusmn;17.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003ePlatelet (10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e189.69\u0026plusmn;53.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e195.67\u0026plusmn;55.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e211.63\u0026plusmn;58.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e202.95\u0026plusmn;68.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.450\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eNeutrophil count \u0026nbsp;(10^9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.05\u0026plusmn;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e3.90\u0026plusmn;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e3.64\u0026plusmn;1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e3.95\u0026plusmn;1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.47\u0026plusmn;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.52\u0026plusmn;1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.69\u0026plusmn;0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e1.88\u0026plusmn;1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eTotal cholesterol (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.10\u0026plusmn;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.00\u0026plusmn;0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.51\u0026plusmn;1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.45\u0026plusmn;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eTSH (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.39\u0026plusmn;1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.48\u0026plusmn;1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.69\u0026plusmn;1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e2.70\u0026plusmn;2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eFT3 (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.58\u0026plusmn;0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.20\u0026plusmn;0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e4.30\u0026plusmn;0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e3.91\u0026plusmn;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eFT4 (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e16.99\u0026plusmn;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e17.08\u0026plusmn;2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.830\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e16.88\u0026plusmn;2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e16.25\u0026plusmn;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.21276595744681%\" style=\"width: 19.8206%;\"\u003e\n \u003cp\u003eTyG Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e8.79\u0026plusmn;0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e8.99\u0026plusmn;0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e9.07\u0026plusmn;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e9.28\u0026plusmn;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.76595744680851%\" style=\"width: 12.5565%;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI, 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.\u003c/p\u003e\n\u003cp\u003eTable 2.Correlation analysis of each parameter with ASMI.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.323232323232325%\" colspan=\"2\" style=\"width: 36.6994%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.323232323232325%\" colspan=\"2\" style=\"width: 36.6994%;\"\u003e\n \u003cp\u003e\u003cstrong\u003efemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003er\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003er\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eHbA1c (％)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eBMI (kg/m2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eAlbumin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eTriglycerides (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eTotalcholesterol(mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.568\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eHDL (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eLDL (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eFBG (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eTSH (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eFT3 (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.19191919191919%\" style=\"width: 21.7078%;\"\u003e\n \u003cp\u003eFT4 (ulU/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e﹣0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.161616161616163%\" style=\"width: 18.3497%;\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCorrelations were analyzed using the Spearman correlation coefficient.\u003c/p\u003e\n\u003cp\u003eTable 3.The association between ASMI and glycosylated hemoglobin was derived by Logistic Regression Models.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.090909090909092%\" style=\"width: 6.0519%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.141414141414142%\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"76.76767676767676%\" colspan=\"6\" style=\"width: 31.9331%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\" style=\"width: 6.0519%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" rowspan=\"2\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"2\" style=\"width: 16.724%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"2\" style=\"width: 16.724%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.742268041237114%\" colspan=\"2\" style=\"width: 11.7784%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.843373493975903%\" style=\"width: 6.0519%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eOdds ratio（95％CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.024096385542169%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eOdds ratio（95％CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.024096385542169%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" style=\"width: 8.3945%;\"\u003e\n \u003cp\u003eOdds ratio（95％CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.024096385542169%\" style=\"width: 3.3188%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\" rowspan=\"2\" style=\"width: 6.0519%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003eNon- Low muscle mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 8.3945%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 3.3188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e\u0026nbsp;Low muscle mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003e1.677（1.219-2.307）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e0.001\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003e1.576（1.134-2.191）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 8.3945%;\"\u003e\n \u003cp\u003e1.511（1.052-2.171）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 3.3188%;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.278350515463918%\" rowspan=\"2\" style=\"width: 6.0519%;\"\u003e\n \u003cp\u003e\u003cstrong\u003efemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.43298969072165%\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003eNon- Low muscle mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.587628865979383%\" style=\"width: 8.3945%;\"\u003e\n \u003cp\u003eref.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.154639175257732%\" style=\"width: 3.3188%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.909090909090908%\" style=\"width: 8.7199%;\"\u003e\n \u003cp\u003e\u0026nbsp;Low muscle mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003e1.202（0.974-1.482）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e0.086\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 12.6894%;\"\u003e\n \u003cp\u003e1.155（0.923-1.444）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 4.0346%;\"\u003e\n \u003cp\u003e0.207\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.59090909090909%\" style=\"width: 8.3945%;\"\u003e\n \u003cp\u003e1.053(0.792-1.401)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.681818181818182%\" style=\"width: 3.3188%;\"\u003e\n \u003cp\u003e0.722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eModel 1: adjusted for Age, BMI, and HbA1c .\u003c/p\u003e\n\u003cp\u003eModel 2:adjusted for covariates in Model 1 plus Diabetic nephropathy ,Diabetic retinopathy ,Diabetic peripheral neuropathy ,Hypertension .\u003c/p\u003e\n\u003cp\u003eModel 3: adjusted for covariates in Model 2 plus FBG,FT3,TyG Index.\u003c/p\u003e\n\u003cp\u003eBMI, body mass index;HbA1c,glycosylated hemoglobin;FBG，fasting blood sugar；FT3 , free triiodothyronine;TyG Index,Triglyceride-Glucose Index.\u003c/p\u003e\n\u003cp\u003eTable 4.Multivariate Regression analysis of the risk of muscle mass loss associated with glycemic control.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.244897959183673%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.673469387755105%\" colspan=\"2\" style=\"width: 31.0039%;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.183673469387756%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.673469387755105%\" colspan=\"2\" style=\"width: 31.0039%;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003eOdds ratio（95％CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003eOdds ratio（95％CI）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003eHbA1c\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e＜6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e1.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003eref\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e1.000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e6.5-6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e3.919（0.772-19.885）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.099\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e1.185(0.279-5.043)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.818\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e7.0-7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e5.777（1.024-32.596）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.047\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e1.015(0.261-3.948)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.983\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.5%\" style=\"width: 11.6142%;\"\u003e\n \u003cp\u003e\u0026ge;8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e9.446（1.978-45.105）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.375%\" style=\"width: 8.7598%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.083333333333332%\" style=\"width: 25.1969%;\"\u003e\n \u003cp\u003e1.699(0.443-6.512)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.25%\" style=\"width: 5.8071%;\"\u003e\n \u003cp\u003e0.439\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMultivariate analysis of the association between different glycated hemoglobin levels and SMI in Model 3.ref.reference\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Old people, Gender differences, Muscle mass, Glycemic control","lastPublishedDoi":"10.21203/rs.3.rs-3747556/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3747556/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe 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.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis 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\".\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere 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\u0026ndash;2.171], p\u0026thinsp;=\u0026thinsp;0.026). When HbA1c levels were further disaggregated, multiple regression analyses showed adverse effects on muscle mass when HbA1c was \u0026gt;\u0026thinsp;7% in men (7%\u0026lt; HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;8%, OR\u0026thinsp;=\u0026thinsp;5.78 [95%CI: 1.024\u0026ndash;32.596], p\u0026thinsp;=\u0026thinsp;0.047; HbA1c\u0026thinsp;\u0026gt;\u0026thinsp;8%, OR\u0026thinsp;=\u0026thinsp;9.45 [95%CI: 1.978\u0026ndash;45.105], p\u0026thinsp;=\u0026thinsp;0.005). However, no association between HbA1c and muscle mass was observed among females.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHigh 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.\u003c/p\u003e","manuscriptTitle":"Gender differences in the relationship between glycemic control and muscle mass in patients with type 2 diabetes mellitus：A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 17:13:31","doi":"10.21203/rs.3.rs-3747556/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"486411db-3a19-465e-9f16-66360721b88b","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-02T17:13:33+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-02 17:13:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3747556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3747556","identity":"rs-3747556","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}