Association of T2DM、Serum Glucose、HbA1c With Lumbar Spine Bone Mineral Density in 40-59 years adults: A Cross Sectional Study Based on the 2011-2018 NHANES Database

Association of T2DM、Serum Glucose、HbA1c With Lumbar Spine Bone Mineral Density in 40-59 years adults: A Cross Sectional Study Based on the 2011-2018 NHANES Database | 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 Association of T2DM、Serum Glucose、HbA1c With Lumbar Spine Bone Mineral Density in 40-59 years adults: A Cross Sectional Study Based on the 2011-2018 NHANES Database Bo Liu, Jingshuang Liu, Junpeng Pan, Hui Zong, Chengliang Zhao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-997527/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 7 You are reading this latest preprint version Abstract Backgrounds: Our purpose is to discuss the relationship among the status and duration of T2DM, serum glucose, glycosylated hemoglobin(HbA1c), and lumbar spine bone mineral density (LSBMD). Methods: We selected participants whose age was 40-59 in the NHANES of 2011-2018 for a cross-sectional study. We used the multiple linear regression model to evaluate the status and duration of T2DM, serum glucose, HbA1c, and LSBMD had a linear correlation. We used the smooth curve fitting and threshold effect methods to explore the potential curvilinear relationship and inflection point, further analyzed the subgroups stratified by genders and race and completed the curve fitting. Result: Finally, 5,329 people met the standard. Finally, we found that the positively correlation between the status of T2DM and the LSBMD, however, the duration of T2DM was not associated with the LSBMD.We further used the smooth curve fitting method to explore. And then we found that blood glucose and level of HbA1c had a curvilinear relationship with the BMD of the lumbar spine in the model. The curve was U-shaped. After the saturation effect and threshold effect analysis, the inflection point was 7.77mmol/L and 5.4%, respectively. According to the further subgroup analysis, we found that the blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in female non-Hispanic black people and Mexican Americans, they had the relationship of a U-shaped curve with the BMD of the lumbar spine. Conclusion: The BMD of the lumbar spine of middle-aged people suffering from T2DM was significantly higher than those who do not suffer from diabetes. However, the duration of T2DM was not associated with the LSBMD.Generally speaking, blood glucose and level of HbA1c had a curvilinear relationship with the BMD of the lumbar spine. The curve was U-shaped (The inflection point was 7.77mmol/L and 5.4%, respectively). The blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in the female non-Hispanic black people and Mexican Americans, they had the relationship of a U-shaped curve with the BMD of the lumbar spine. Orthopedic Surgery Type 2 diabetes mellitus lumbar spine bone mineral density serum glucose HbA1c cross sectional study NHANES database Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction With the increase of the average longevity of people and the aging of society, diabetes and osteoporosis have become a hot topic of research. Generally, the diabetes of teenagers under the age of 20 and children is often T1DM. However, there are some exceptions. The diabetes of most middle-aged and elderly people whose age is above 40 is T2DM [ 1 ].Based on the BMD of the lumbar spine, we can diagnose osteoporosis. T value is the commonly used expression value of the BMD in medicine. When the T value is less than -2.5, it indicates that the patient should be alert for the phenomenon of osteoporosis and receive the treatment timely and as early as possible. Diabetes may cause a significant increase in the risk of osteoporosis, which has been proved[ 2 ].The BMD of T1DM patients decreases. However, the BMD of T2DM patients is usually normal and even becomes slightly higher [ 3 – 5 ]. The bone turnover of diabetes patients decreases and properties of bone materials and bone microstructure change. The NHANES is a cross-sectional survey based on the crowds. It aims to collect the information about health and nutrition of families and populations in the United States. In the NHANES, the stratified multi-stage sampling design was used to obtain the representative samples of American residents.Many researchers have used a large amount of data for cross-sectional research.However, up to now, the correlation between the serum glucose, HbA1c and BMD is unknown. The purpose of this study is to explore the correlation between the status and duration of T2DM, serum glucose, and HbA1c and LSBMD.It also could provide a basis for the control of chronic complications of diabetes. Methods We summarized the NHANES data of 4 cycles including 2011-2012; 2013-2014; 2015-2016; 2017-2018. The inclusion and exclusion criteria were as follows. The age range is 40-59; It were excluded for the data of LSBMD, serum glucose, or HbA1c was missing; and the same for other missing covariate values. Finally, 5,329 research objects meeting the standard were included. NHANES protocol was approved by the Review Committee of the National Health Statistics Ethics Research Center. The written informed consent of all the adult participants was obtained. For participants under the age of 18, the agreement of parents or guardians was required. Variables The exposure variables included the status of T2DM, the duration, serum glucose, and HbA1c. The status of T2DM is defined as “The doctor told that he/she suffered from diabetes.” The duration is calculated as the age of participating the NHANES minus the age when first told you had diabetes. The serum glucose and HbA1c were both obtained from the part of“Laboratory Data”in NHANES, including BIOPRO_G; BIOPRO_H; BIOPRO_I; BIOPRO_J and GHB_G; GHB_H; GHB_I; GHB_J. Serum glucose (non-fasting) was measured by means of a Roche/Hitachi cobas C Chemistry Analyzer (Roche Diagnostics, Indianapolis, IN) or a Roche/Hitachi Modular P Chemistry Analyzer. HbA1c was measured on a Tosoh Automated Analyzer HLC-723G8 (Tosoh Medics, Inc., San Francisco, CA) or a Tosoh G7 Automated HPLC Analyzer. The BMD of the lumbar spine was an outcome variable. The spine scans were acquired on Hologic Discovery model A densitometers (Hologic, Inc., Bedford, Massachusetts), using software version Apex 3.2. The radiation exposure from DXA for the spine scan is extremely low at less than 20 uSv. All scans in the “DXXSPN_G; DXXSPN_H; DXXSPN_I; DXXSPN_J” file were analyzed with Hologic APEX version 4.0 software. The following data was confounding variables. Age, gender, race, family income, poverty rate, educational level, smoking at least 100 cigarettes in life, active entertainment activities, body mass index (BMI), and other information were obtained by self-reporting. At the same time, in the standardized biochemical test, data such as serum sodium, serum potassium, serum phosphorus, alkaline phosphatase, serum uric acid, blood urea nitrogen, serum creatinine, total protein, total cholesterol, and serum calcium was obtained. Statistical method R version 3.4.3 software package ( http:// www.R-project.org ) and EmpowerStats ( http:// www.empowerstats.com ) were used. If the P-value is less than 0.05, the difference is statistically significant. The multivariable logistic regression model was used to evaluate the relationship between the status and duration of T2DM, serum glucose, and HbA1c and BMD of the lumbar spine. We built 3 models. In Model 1, covariates were not adjusted; in the Model 2, age, gender and race were adjusted; and in the Model 3, all the covariates were adjusted. At the same time, according to gender, T2DM status,duration, serum glucose, and HbA1c, the subgroup analysis was made. The smooth curve fitting was used to explore the non-linear relationship. We further used the two-segment linear regression model to calculate the inflection points. Finally, we further made the subgroup analysis according to the relationship between serum glucose and HbA1c and BMD of the lumbar spine in different genders and races. We completed the curve fitting. Results The Demographic of Cohort with and without Type 2 Diabetes As shown in Table 1 , finally, 5,329 people met the standard, including 4,639 non-diabetes patients and 690 diabetes patients. Compared with non-diabetes patients, T2DM patients were older(P<0.001). Their BMI and LSBMD were higher (P<0.001). Adults suffering from T2DM had few entertainment activities and low family income, poverty rate, and education level. Among them, differences between the two groups were significant in alkaline phosphatase, total cholesterol, blood urea nitrogen, serum sodium, serum potassium, serum calcium, blood glucose, and HbA1c in the standard serum biochemical test (P<0.001). Table 1 Weighted Characteristics of Study Sample with and without Type 2 Diabetes Type 2 Diabetes(690) Non-Diabetes(4639) P-value P-value* Age 50.76 ± 5.37 49.07 ± 5.71 <0.001 <0.001 Gender 0.084 - Male 360 (52.17%) 2257 (48.65%) Famale 330 (47.83%) 2382 (51.35%) Race <0.001 - Mexican American 130 (18.84%) 637 (13.73%) Other Hispanic 74 (10.72%) 494 (10.65%) Non-Hispanic White 174 (25.22%) 1638 (35.31%) Non-Hispanic Black 186 (26.96%) 1014 (21.86%) Other Race 126 (18.26%) 856 (18.45%) BMI 33.37 ± 7.60 29.16 ± 6.49 <0.001 <0.001 Duration 8.88 ± 8.27 / Education <0.001 - Less than 9th grade 79 (11.45%) 356 (7.67%) 9-11th grade 110 (15.94%) 571 (12.31%) High school graduate 152 (22.03%) 1025 (22.10%) Some college or AA degree 219 (31.74%) 1358 (29.27%) College graduate or above 130 (18.84%) 1329 (28.65%) Ratio of family income to poverty 2.36 ± 1.59 2.78 ± 1.69 <0.001 <0.001 Vigorous Activities <0.001 - Yes 103 (14.93%) 1087 (23.43%) No 587 (85.07%) 3552 (76.57%) Smoked 0.268 - Yes 308 (44.64%) 1967 (42.40%) No 382 (55.36%) 2672 (57.60%) Standard Biochemical Examination HbA1c 7.94 ± 2.12 5.58 ± 0.67 <0.001 <0.001 Serum glucose 9.35 ± 4.92 5.38 ± 1.37 <0.001 <0.001 Alkaline Phosphatase 77.02 ± 26.39 69.98 ± 23.98 <0.001 <0.001 Blood Urea Nitrogen 5.26 ± 2.56 4.69 ± 1.64 <0.001 <0.001 Serum Cholesterol 4.90 ± 1.28 5.24 ± 1.04 <0.001 <0.001 Serum Creatinine 84.79 ± 84.90 76.09 ± 27.72 <0.001 0.329 Phosphorus 1.20 ± 0.19 1.19 ± 0.18 0.032 0.124 Uric Acid 324.77 ± 89.53 318.51 ± 83.43 0.069 0.155 Sodium 138.40 ± 2.83 139.41 ± 2.28 <0.001 <0.001 Potassium 4.04 ± 0.37 3.95 ± 0.33 <0.001 <0.001 Total Proten 71.79 ± 5.03 71.46 ± 4.48 0.075 0.126 Total Calcium 2.34 ± 0.09 2.33 ± 0.09 <0.001 <0.001 Lumbar Spine BMD 1.05 ± 0.17 1.02 ± 0.16 <0.001 <0.001 Results in the table: mean + SD / N (%) P value *: if it is a continuous variable, it shall be obtained by Kruskal Wallis rank sum test. If the theoretical number of counting variables is less than 10, it shall be obtained by Fisher exact probability test. Relationship between the status and duration of T2DM and lumbar spine BMD As shown in Table 2, we finally built three models. Among them, Model 1: β = 0.039, 95% CI: 0.025-0.054, P<0.00001; Model 2 : β = 0.043, 95% CI: 0.029-0.057, P<0.00001; and Model 3 (full-adjusted model): β = 0.023, 95% CI: 0.004-0.041, P=0.01829. We can know that they were all positively correlated. Table 2 Associations Between the status of T2DM and Lumbar Spinal Bone Mineral Density (g/cm 2 ) Exposure Non-adjusted Model Adjust Model I Adjust Model II Non-Diabetes Reference Reference Reference Type 2 Diabetes 0.039 (0.025, 0.054) <0.00001 0.043 (0.029, 0.057) <0.00001 0.023 (0.004, 0.041) 0.01829 Male with Non-Diabetes Reference Reference Reference Male with Type 2 Diabetes 0.050 (0.030, 0.070) <0.00001 0.045 (0.025, 0.065) <0.00001 0.015 (-0.013, 0.042) 0.29783 Famale with Non-Diabetes Reference Reference Reference Famale with Type 2 Diabetes 0.027 (0.007, 0.047) 0.00770 0.038 (0.019, 0.058) 0.00009 0.032 (0.007, 0.057) 0.01349 Data in the table: β ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable: Type 2 Diabetes Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c; Serum glucose;Alkaline Phosphatase; Blood Urea Nitrogen; Serum Cholesterol; Serum Creatinine; Phosphorus;Uric Acid; Sodium; Potassium; Total Proten; Total Calcium According to the subgroup stratified by gender, we had the following further findings. For men suffering from diabetes, Model 1: β = 0.050, 95% CI: 0.030-0.070, P<0.00001; Model 2: β = 0.045 95% CI: 0.025-0.065, P<0.00001; and Model 3: β = 0.015 95% CI:-0.013-0.042, P=0.29783. For women suffering from diabetes, Model 1: β = 0.027, 95% CI: 0.007-0.047, P=0.0077; Model 2: β = 0.038, 95% CI: 0.019-0.058, P=0.00009; and Model 3: β = 0.032, 95% CI: 0.007-0.057, P=0.01349. In summary, the positive correlation between the two was relatively stable. However, as shown in Table 3, there was no significant association between disease duration of T2DM and LSBMD in both genders in all three models (in the Model 3, for males: β = 0.001, 95% CI:-0.0015–0.0035, P=0.433215; for females: β= -0.0018, 95% CI: -0.0037–0.0001,P=0.061801). Table 3 Associations Between T2DM Duration (Year) and Lumbar Bone Mineral Density (g/cm 2 ) Model Non-adjusted Model Adjust Model I Adjust Model II Total -0.0003 (-0.0018, 0.0013) 0.742754 -0.0004 (-0.0019, 0.0011) 0.613685 -0.0007 (-0.0022, 0.0008) 0.363552 Male 0.0010 (-0.0015, 0.0035) 0.432817 0.0003 (-0.0021, 0.0028) 0.784566 0.0010 (-0.0015, 0.0035) 0.433215 Famale -0.0013 (-0.0032, 0.0006) 0.197111 -0.0011 (-0.0029, 0.0007) 0.226405 -0.0018 (-0.0037, 0.0001) 0.061801 Data in the table: β ( 95%CI) Pvalue; Outcome variable: lumbar spine BMD; Exposure variable: Duration Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Vigorous Activities; Smoking; HbA1c; Serum glucose; Alkaline Phosphatase; Blood Urea Nitrogen; Serum Cholesterol; Serum Creatinine; Phosphorus; Uric Acid; Sodium; Potassium; Total Proten; Total Calcium Relationship between serum glucose and lumbar spine BMD As shown in Table 4 , we built 3 models. Among them, Model 1: β = 0.004, 95% CI: 0.002-0.005,P=0.00029; Model 2: β = 0.005, 95%CI: 0.003-0.006,P=<0.00001; and Model 3: β = 0.004, 95%CI: 0.000-0.007,P=0.02742.We found that there seems to be a slightly linear relationship. We further explored the relationship between the quartile of serum glucose and BMD of the lumbar spine. Finally,We found that they did not have a linear correlation(Model 1:P for trend= 0.734, Model 2:P for trend= 0.092, and Model 3:P for trend= 0.909). We further used the smooth curve fitting method to directly find that they had the relationship of a U-shaped curve (Figure 1 ). According to the saturation effect and threshold effect analysis, the inflection point was 7.77 mmol/L and the log-likelihood ratio P=0.031༜0.05 (Table 5 ). It indicated that the curvilinear relationship was established. The subgroups of different genders and races were analyzed. According to the smooth curve fitting, the serum glucose of male ,non-Hispanic whites, Spanish, and other races had a line relationship with the BMD of the lumbar spine. The serum glucose of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. (Figure 3 , Figure 4 ) Table 4 Associations Between Serum Glucose (mmol/L) and Lumbar Spinal Bone Mineral Density (g/cm 2 ) Exposure Non-adjusted Adjust I Adjust II Serum Glucose 0.004 (0.002, 0.005) 0.00029 0.005 (0.003, 0.006) <0.00001 0.004 (0.000, 0.007) 0.02742 Serum Glucose Q1 Reference Reference Reference Q2 0.003 (-0.009, 0.015) 0.61733 0.007 (-0.004, 0.019) 0.21283 0.011 (-0.001, 0.023) 0.06510 Q3 -0.005 (-0.017, 0.006) 0.36505 0.000 (-0.012, 0.012) 0.99526 -0.000 (-0.012, 0.012) 0.98841 Q4 0.006 (-0.007, 0.018) 0.37293 0.014 (0.002, 0.026) 0.02401 0.003 (-0.011, 0.017) 0.66512 P for trend 0.734 0.092 0.909 Data in the table: β ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Serum Glucose (mmol/L) Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium Table 5 Nonlinearity addressing of Serum glucose(mmol/L)and Lumbar spinal Bone Mineral Density (g/cm 2 ) Outcome: β 95%CI P value Model 1 : Fitting model by standard linear regression 0.004 (0.000, 0.007) 0.0274 Model2 : Fitting model by two-piecewise linear regression Inflection point Inflection point 7.77 7.77 0.007 (0.002, 0.011) 0.0021 P for log likelyhood rati o 0.031 Data in the table: β ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Serum Glucose (mmol/L) Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium Relationship between HbA1c and lumbar spine BMD As shown in Table 6 , we built 3 models. Among them, Model 1: β = 0.007, 95% CI: 0.004-0.011,P=0.00018; Model 2: β = 0.009, 95% CI: 0.005-0.013,P<0.00001; and Model 3: β = 0.001, 95% CI:-0.007-0.008,P=0.87344. We explored the relationship between the quartile of HbA1c and BMD of the lumbar spine. We found that they did not have a linear correlation((Model 1:P for trend= 0.332, Model 2:P for trend= 0.843, and Model 3:P for trend= 0.016 ). We further used the smooth curve fitting method to directly find that they had the relationship of a U-shaped curve (Figure 2 ). According to the saturation effect and threshold effect analysis, the inflection point was 5.4% and the log-likelihood ratio P༜0.001 (Table 7 ). It indicated that the Curve relation was established. We further made the subgroup analysis with gender and race. According to the smooth curve fitting, HbA1c of male,non-Hispanic whites and other Spanish had a line relationship with the BMD of the lumbar spine. The HbA1c of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. (Figure 3 , Figure 4 ) Table 6 Associations Between Glycohemoglobin (%) and Lumbar Spinal Bone Mineral Density (g/cm 2 ) Exposure Non-adjusted Adjust I Adjust II HbA1c 0.007 (0.004, 0.011) 0.00018 0.009 (0.005, 0.013) <0.00001 0.001 (-0.007, 0.008) 0.87344 HbA1c Q1 Reference Reference Reference Q2 -0.029 (-0.040, -0.018) <0.00001 -0.023 (-0.034, -0.011) 0.00008 -0.020 (-0.031, -0.008) 0.00081 Q3 -0.031 (-0.044, -0.019) <0.00001 -0.024 (-0.037, -0.012) 0.00013 -0.020 (-0.033, -0.007) 0.00328 Q4 -0.006 (-0.019, 0.007) 0.34641 -0.001 (-0.014, 0.012) 0.90267 -0.018 (-0.034, -0.002) 0.02599 P for trend 0.332 0.843 0.016 Data in the table: β ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Glycohemoglobin (%);Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium Table 7 Nonlinearity addressing of Glycohemoglobin (%) and Lumbar Spinal Bone Mineral Density (g/cm 2 ) Outcome: β 95%CI P value Model 1 : Fitting model by standard linear regression 0.001 (-0.007, 0.008) 0.8734 Model2 : Fitting model by two-piecewise linear regression Inflection point Inflection point 5.4 5.4 0.006 (-0.002, 0.015) 0.1374 P for log likelyhood ratio <0.001 Data in the table: β ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Glycohemoglobin (%); Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium Discussion The morbidity of diabetes has the trend of increasing around the world. 422 million people suffer from diabetes worldwide. 90% of them suffer from T2DM, which is characterized by insulin resistance. T1DM decreases. It is mainly characterized by insulin deficiency. Children and teenagers are the main crowds of diabetes. Diabetes patients often have chronic complications of the cardiovascular system, eyes, kidneys, nervous system, and other systems. In particular, bone strength is also impaired[ 6 – 9 ]. However, up to now, researchers do not know the correlation between the fluctuation of serum glucose and the content of HbA1c and BMD. In this study, the relationship between T2DM, serum glucose, and HbA1c and BMD of the lumbar spine was explored. In the study, we found that compared with non-T2DM patients T2DM patients had a higher BMD of the lumbar spine, which was positively correlated. Many studies proved that T1DM patients had a lower BMD compared to normal people at the same age and T2DM patients had a normal or higher BMD [ 10 – 20 ]. Our study also provided evidence for the conclusion, perhaps because T2DM patients had insulin resistance. Insulin is a kind of synthetic hormone. Too much hormone in their body promoted the increase of bone metabolism and synthesis, so the BMD is higher. Some researchers believed that BMD was positively correlated to BMI. We can believe that the increase of BMD is a physiological phenomenon to adapt to the current physical load [ 6 , 21 , 22 ]. However, the risk of fracture of T1DM or T2DM patients is higher than that of normal people [ 4 , 6 , 23 – 26 ]. Most T2DM patients are fat. However, the high BMD caused by obesity may not necessarily provide better protection for fracture. There may be a BMI threshold value, beyond which the bones cannot adapt any more. Therefore, the special parts of the body (such as wrist joints, humerus, etc.) may have a fracture. According to this study, blood glucose and HbA1c have a non-linear relationship with BMD of the lumbar spine. According to the smooth curve effect, we found that they had a relationship of a U-shaped curve. Further, according to the saturation effect analysis, we found that the test effect value of the log-likelihood ratio of the two curves was 0.031 and less than 0.001, respectively. The inflection point of the two curves was 7.77mmol/L and 5.4%, respectively. In a Chinese study, Xu et al. [ 27 ] separated monocytes from the marrow of C57BL/6 mice. When the combination of hyperglycemia and hyperinsulinemia was simulated, the osteoclast differentiation and expression of marker genes were down-regulated. Finally, the BMD became higher. However, Jia et al. [ 3 ] found in their study that BMD and BMC of the T2DM group were lower than those of the normal group. Our study suggested that blood sugar content and BMD of the lumbar spine had a curvilinear relationship. Besides, when the blood sugar content was 7.77mmol/L, the BMD of the lumbar spine was the lowest. In our study, we further analyzed subgroups of different genders and races. According to the smooth curve fitting, the blood sugar content of male non-Hispanic whites, Spanish, and other races had a line relationship with the BMD of the lumbar spine. The blood sugar content of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. HbAlc reflects the control of average blood glucose in the last 2-3 months and is not affected by glycometabolism and eating[ 17 , 28 ]. The higher HbA1c is, the poorer the control of blood glucose is. At present, many scholars have different opinions on the correlation between HbA1c and BMD. Guo et al. [ 29 ] found that when HbA1c was greater than 8.0% the BMD of the neck of the femur significantly decreased. However, Majima et al.[ 15 ] believed that the BMD of the distal radius of men and women and that of the neck of the femur of women gradually decreased with the increase of HbA1c. Some researchers even found that the BMD and HbA1c had no clear relationship[ 30 , 31 ]. However, in our study, we found that HbA1c and BMD of the lumbar spine had a curvilinear relationship. Besides, when HbA1c was 5.4%, BMD of the lumbar spine was the lowest. Gender and race were used for further subgroup analysis and smooth curve fitting. We found that the content of HbA1c of male non-Hispanic whites and other Spanish had a line relationship with the BMD of the lumbar spine. The content of HbA1c of female non-Hispanic black people, other Spanish, and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. Limitation However, our study also has the following limitations. First, the crowds suffering from diabetes were defined by the self-reporting of diabetes, which caused a big bias. Second, this study is a cross-sectional study. The above conclusion only shows that they are correlated, but they do not have a causal relationship. Finally, in our study, only some covariates were included, As far as I know, BMD is used as the outcome variable. We only selected lumbar BMD, including hip joint BMD and rib BMD. However, in other year cycles, hip joint BMD has some and some do not. The data of bone turnover markers are very old. There are cycles, but not later. The fracture data only passed the questionnaire and was not detailed. We can only hope that the next researcher will continue to study and make more detailed results. Such as whether there is a correlation between the use of antidiabetic drugs and lumbar spine BMD in diabetic patients. If possible, all the confounding factors should be included. Conclusion The BMD of the lumbar spine of middle-aged people suffering from T2DM was significantly higher than that of people not suffering from diabetes. Generally speaking, blood glucose and level of HbA1c had a curvilinear relationship with BMD. The curve was U-shaped (The inflection point was 7.77mmol/L and 5.4%). The blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in female non-Hispanic black people and Mexican Americans, they had a relationship of a U-shaped curve with the BMD of the lumbar spine. Abbreviations T2DM：Type 2 diabetes mellitus；LSBDN：Lumbar spinal bone mineral density；NHANES; National Health and Nutrition EXamination Survey; HbA1c: Glycosylated hemoglobin; OR: Odds ratio; Cl: Confidence interval. Declarations Acknowledgements None. Authors’ contributions BL performed the data analysis. BL and JSL wrote the manuscript. JSL,JPP,HZ and CLZ contributed to the manuscript revise. BL, JSL and CLZ contributed to literature search and data extraction. BL, CLZ and ZJW conceived and designed the study. All authors have read and approved the final version of the manuscript. Funding This study was financially supported by the Department of Science Technology of Shandong Province for Key Technology Research and Development Program of Shandong（CN）（NO. 2018GSF118080）and Qingdao Municipal Science and Technology Bureau for demotic science ar technology program（NO. 19-6-1-16-nsh） Availability of data and materials The authors thank the staff and participants of the NHANES study for their valuable contributions Ethics approval and consent to participate The National Center for health statistics ethical review board approved all NHANES protocols, and written informed consent was obtained from all participants. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References American Diabetes A: Diagnosis and classification of diabetes mellitus . Diabetes Care 2012, 35 Suppl 1 :S64-71. Ge B, Lu S, Lei S: The obesity indices mediate the relationships of blood lipids and bone mineral density in Chinese elders . Molecular and cellular probes 2021, 56 :101705. Jia X, Liu L, Wang R, Liu X, Liu B, Ma N, Lu Q: Relationship of Two-Hour Plasma Glucose and Abdominal Visceral Fat with Bone Mineral Density and Bone Mineral Content in Women with Different Glucose Metabolism Status . Diabetes Metab Syndr Obes 2020, 13 :851-858. Melton LJ, 3rd, Leibson CL, Achenbach SJ, Therneau TM, Khosla S: Fracture risk in type 2 diabetes: update of a population-based study . J Bone Miner Res 2008, 23 (8):1334-1342. Zhao X, Zhang XM, Yuan N, Yu XF, Ji LN: Associations of Bone Mineral Density and Bone Metabolism Indices with Urine Albumin to Creatinine Ratio in Chinese Patients with Type 2 Diabetes . Exp Clin Endocrinol Diabetes 2019, 127 (1):50-55. Starup-Linde J, Hygum K, Langdahl BL: Skeletal Fragility in Type 2 Diabetes Mellitus . Endocrinol Metab (Seoul) 2018, 33 (3):339-351. Hua F: New insights into diabetes mellitus and its complications: a narrative review . Ann Transl Med 2020, 8 (24):1689. Lee HS, Hwang JS: Impact of Type 2 Diabetes Mellitus and Antidiabetic Medications on Bone Metabolism . Curr Diab Rep 2020, 20 (12):78. Haw J, Shah M, Turbow S, Egeolu M, Umpierrez G: Diabetes Complications in Racial and Ethnic Minority Populations in the USA . Current diabetes reports 2021, 21 (1):2. Vestergaard P: Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes--a meta-analysis . Osteoporos Int 2007, 18 (4):427-444. Moayeri A, Mohamadpour M, Mousavi SF, Shirzadpour E, Mohamadpour S, Amraei M: Fracture risk in patients with type 2 diabetes mellitus and possible risk factors: a systematic review and meta-analysis . Ther Clin Risk Manag 2017, 13 :455-468. Ma L, Oei L, Jiang L, Estrada K, Chen H, Wang Z, Yu Q, Zillikens MC, Gao X, Rivadeneira F: Association between bone mineral density and type 2 diabetes mellitus: a meta-analysis of observational studies . Eur J Epidemiol 2012, 27 (5):319-332. Martins JM, Aranha P: Bone turnover and bone mineral density in old persons with type 2 diabetes . J Clin Transl Endocrinol 2018, 14 :12-18. Gerdhem P, Isaksson A, Akesson K, Obrant KJ: Increased bone density and decreased bone turnover, but no evident alteration of fracture susceptibility in elderly women with diabetes mellitus . Osteoporos Int 2005, 16 (12):1506-1512. Majima T, Komatsu Y, Yamada T, Koike Y, Shigemoto M, Takagi C, Hatanaka I, Nakao K: Decreased bone mineral density at the distal radius, but not at the lumbar spine or the femoral neck, in Japanese type 2 diabetic patients . Osteoporos Int 2005, 16 (8):907-913. Oei L, Zillikens MC, Dehghan A, Buitendijk GH, Castano-Betancourt MC, Estrada K, Stolk L, Oei EH, van Meurs JB, Janssen JA et al : High bone mineral density and fracture risk in type 2 diabetes as skeletal complications of inadequate glucose control: the Rotterdam Study . Diabetes Care 2013, 36 (6):1619-1628. Steffes M, Cleary P, Goldstein D, Little R, Wiedmeyer HM, Rohlfing C, England J, Bucksa J, Nowicki M: Hemoglobin A1c measurements over nearly two decades: sustaining comparable values throughout the Diabetes Control and Complications Trial and the Epidemiology of Diabetes Interventions and Complications study . Clin Chem 2005, 51 (4):753-758. Yang Y, Liu G, Zhang Y, Xu G, Yi X, Liang J, Zhao C, Liang J, Ma C, Ye Y et al : Association Between Bone Mineral Density, Bone Turnover Markers, and Serum Cholesterol Levels in Type 2 Diabetes . Front Endocrinol (Lausanne) 2018, 9 :646. Gu LJ, Lai XY, Wang YP, Zhang JM, Liu JP: A community-based study of the relationship between calcaneal bone mineral density and systemic parameters of blood glucose and lipids . Medicine (Baltimore) 2019, 98 (27):e16096. de Waard EAC, de Jong JJA, Koster A, Savelberg H, van Geel TA, Houben A, Schram MT, Dagnelie PC, van der Kallen CJ, Sep SJS et al : The association between diabetes status, HbA1c, diabetes duration, microvascular disease, and bone quality of the distal radius and tibia as measured with high-resolution peripheral quantitative computed tomography-The Maastricht Study . Osteoporos Int 2018, 29 (12):2725-2738. Cherukuri L, Kinninger A, Birudaraju D, Lakshmanan S, Li D, Flores F, Mao S, Budoff M: Effect of body mass index on bone mineral density is age-specific . Nutrition, metabolism, and cardiovascular diseases : NMCD 2021, 31 (6):1767-1773. Mesinovic J, Jansons P, Zengin A, de Courten B, Rodriguez A, Daly R, Ebeling P, Scott D: Exercise attenuates bone mineral density loss during diet-induced weight loss in adults with overweight and obesity: A systematic review and meta-analysis . Journal of sport and health science 2021. Gagnon C, Magliano DJ, Ebeling PR, Dunstan DW, Zimmet PZ, Shaw JE, Daly RM: Association between hyperglycaemia and fracture risk in non-diabetic middle-aged and older Australians: a national, population-based prospective study (AusDiab) . Osteoporos Int 2010, 21 (12):2067-2074. Hothersall EJ, Livingstone SJ, Looker HC, Ahmed SF, Cleland S, Leese GP, Lindsay RS, McKnight J, Pearson D, Philip S et al : Contemporary risk of hip fracture in type 1 and type 2 diabetes: a national registry study from Scotland . J Bone Miner Res 2014, 29 (5):1054-1060. Bonds DE, Larson JC, Schwartz AV, Strotmeyer ES, Robbins J, Rodriguez BL, Johnson KC, Margolis KL: Risk of fracture in women with type 2 diabetes: the Women's Health Initiative Observational Study . J Clin Endocrinol Metab 2006, 91 (9):3404-3410. Looker AC, Eberhardt MS, Saydah SH: Diabetes and fracture risk in older U.S. adults . Bone 2016, 82 :9-15. Xu F, Ye YP, Dong YH, Guo FJ, Chen AM, Huang SL: Inhibitory effects of high glucose/insulin environment on osteoclast formation and resorption in vitro . J Huazhong Univ Sci Technolog Med Sci 2013, 33 (2):244-249. Qi J, Su Y, Song Q, Ding Z, Cao M, Cui B, Qi Y: Reconsidering the HbA1c Cutoff for Diabetes Diagnosis Based on a Large Chinese Cohort . Exp Clin Endocrinol Diabetes 2021, 129 (2):86-92. Guo L, Gao Z, Ge H: Effects of serum 25-hydroxyvitaminD level on decreased bone mineral density at femoral neck and total hip in Chinese type 2 diabetes . PLoS One 2017, 12 (11):e0188894. Yao X, Xu X, Jin F, Zhu Z: The Correlation of Type 2 Diabetes Status with Bone Mineral Density in Middle-Aged Adults . Diabetes Metab Syndr Obes 2020, 13 :3269-3276. Iki M, Fujita Y, Kouda K, Yura A, Tachiki T, Tamaki J, Winzenrieth R, Sato Y, Moon JS, Okamoto N et al : Hyperglycemia is associated with increased bone mineral density and decreased trabecular bone score in elderly Japanese men: The Fujiwara-kyo osteoporosis risk in men (FORMEN) study . Bone 2017, 105 :18-25. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Major revision 17 Dec, 2021 Reviews received at journal 24 Nov, 2021 Reviewers invited by journal 21 Oct, 2021 Editor assigned by journal 21 Oct, 2021 Submission checks completed at journal 20 Oct, 2021 Editor invited by journal 20 Oct, 2021 First submitted to journal 19 Oct, 2021 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-997527","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":58100872,"identity":"b437ef96-bf12-415c-90fa-c83855771030","order_by":0,"name":"Bo Liu","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Liu","suffix":""},{"id":58100873,"identity":"d64b3028-b28e-47fe-a1fa-bd68ae9fa5d4","order_by":1,"name":"Jingshuang Liu","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jingshuang","middleName":"","lastName":"Liu","suffix":""},{"id":58100874,"identity":"36e0f27d-01e5-417c-baea-2d28a5faa167","order_by":2,"name":"Junpeng Pan","email":"","orcid":"","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junpeng","middleName":"","lastName":"Pan","suffix":""},{"id":58100875,"identity":"976ce011-3e06-43e7-be76-2d915ccddbea","order_by":3,"name":"Hui Zong","email":"","orcid":"","institution":"The People's Hospital of Qingyun","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Zong","suffix":""},{"id":58100876,"identity":"b5cc8aab-614d-44f2-9531-64e89042a72e","order_by":4,"name":"Chengliang Zhao","email":"","orcid":"https://orcid.org/0000-0002-2673-3398","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Chengliang","middleName":"","lastName":"Zhao","suffix":""},{"id":58100877,"identity":"74fc69fc-4ac2-4934-89e5-fa90bc45707f","order_by":5,"name":"Zhijie Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYDACZjiD+eCDDxUScvLEa2FnSzacccbC2LCBaOv4ecyEedsqEhkOEFAo386d+LiwzS5P3pnHjJl3nkQCYwPzw0c38GgxOMy72XhmW3Kx4WG2sodzt0nksTOwGRvn4NPCzLtNmncbc+LGZubtBm+3SRQzNvCwSePTIt8M1lIP1MJgJsE7RyKx4QABLQyHwVoOJ85nZjGT5G0gQgvYL7z/jiduYAYF8jEJY8NmAn6R7z+78THPmerE+f2HgVFZUycnz9788DFeh8GtOwBjMeNRhWpdA7EqR8EoGAWjYMQBAC82SH7Be8WMAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-4944-1750","institution":"The Affiliated Hospital of Qingdao University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Zhijie","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2021-10-20 03:19:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-997527/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-997527/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":14813129,"identity":"d9ee21fb-6662-4383-84db-b5ec7f552a78","added_by":"auto","created_at":"2021-10-22 18:47:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":185132,"visible":true,"origin":"","legend":"The association between Serum glucose and total bone mineral density. (A) Each black point represents a sample. (B) Solid rad line represents the smooth curve fit between variables. Blue bands represent the 95% of confidence interval from the fit. ","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-997527/v1/5832c48ca91e2861ea109c0d.jpg"},{"id":14813130,"identity":"4bd1264b-5c3c-489f-9932-f2398aa2bc78","added_by":"auto","created_at":"2021-10-22 18:47:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":192216,"visible":true,"origin":"","legend":"The association between glycosylated hemoglobin and total bone mineral density. （A） Each black point represents a sample. （B） Solid rad line represents the smooth curve fit between variables. Blue bands represent the 95% of confidence interval from the fit.","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-997527/v1/a71bf9cc034cc1341b2bbab6.jpg"},{"id":14813128,"identity":"83468923-e7c4-43b3-9c08-b4a5cbc02988","added_by":"auto","created_at":"2021-10-22 18:47:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":115512,"visible":true,"origin":"","legend":"The associations between serum glucose, glycosylated hemoglobin and LSBDM stratified by gender. ","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-997527/v1/c7057b4a22db8944f74a9c68.jpg"},{"id":14813298,"identity":"f0d79b83-8114-4252-a4ce-facda6e89ed5","added_by":"auto","created_at":"2021-10-22 18:50:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":230233,"visible":true,"origin":"","legend":"The associations between serum glucose, glycosylated hemoglobin and LSBDM stratified by race.","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-997527/v1/75b5897136c3f53fbe99e921.jpg"},{"id":14813299,"identity":"26bc3a44-7315-4282-9d85-2059b1c15fa4","added_by":"auto","created_at":"2021-10-22 18:50:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1349605,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-997527/v1/333bf880-e81a-4952-8f0e-7e31d8c89e87.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eAssociation of T2DM、Serum Glucose、HbA1c With Lumbar Spine Bone Mineral Density in 40-59 years adults: A Cross Sectional Study Based on the 2011-2018 NHANES Database\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith the increase of the average longevity of people and the aging of society, diabetes and osteoporosis have become a hot topic of research. Generally, the diabetes of teenagers under the age of 20 and children is often T1DM. However, there are some exceptions. The diabetes of most middle-aged and elderly people whose age is above 40 is T2DM [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].Based on the BMD of the lumbar spine, we can diagnose osteoporosis. T value is the commonly used expression value of the BMD in medicine. When the T value is less than -2.5, it indicates that the patient should be alert for the phenomenon of osteoporosis and receive the treatment timely and as early as possible.\u003c/p\u003e \u003cp\u003eDiabetes may cause a significant increase in the risk of osteoporosis, which has been proved[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].The BMD of T1DM patients decreases. However, the BMD of T2DM patients is usually normal and even becomes slightly higher [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The bone turnover of diabetes patients decreases and properties of bone materials and bone microstructure change.\u003c/p\u003e \u003cp\u003eThe NHANES is a cross-sectional survey based on the crowds. It aims to collect the information about health and nutrition of families and populations in the United States. In the NHANES, the stratified multi-stage sampling design was used to obtain the representative samples of American residents.Many researchers have used a large amount of data for cross-sectional research.However, up to now, the correlation between the serum glucose, HbA1c and BMD is unknown. The purpose of this study is to explore the correlation between the status and duration of T2DM, serum glucose, and HbA1c and LSBMD.It also could provide a basis for the control of chronic complications of diabetes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe summarized the NHANES data of 4 cycles including 2011-2012; 2013-2014; 2015-2016; 2017-2018. The inclusion and exclusion criteria were as follows. The age range is 40-59; It were excluded for the data of LSBMD, serum glucose, or HbA1c was missing; and the same for other missing covariate values. Finally, 5,329 research objects meeting the standard were included. NHANES protocol was approved by the Review Committee of the National Health Statistics Ethics Research Center. The written informed consent of all the adult participants was obtained. For participants under the age of 18, the agreement of parents or guardians was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe exposure variables included the status of T2DM, the duration, serum glucose, and HbA1c. The status of T2DM is defined as \u0026ldquo;The doctor told that he/she suffered from diabetes.\u0026rdquo; The duration is calculated as the age of participating the NHANES minus the age when first told you had diabetes. The serum glucose and HbA1c were both obtained from the part of\u0026ldquo;Laboratory Data\u0026rdquo;in NHANES, including BIOPRO_G; BIOPRO_H; BIOPRO_I; BIOPRO_J and GHB_G; GHB_H; GHB_I; GHB_J. Serum glucose (non-fasting) was measured by means of a Roche/Hitachi cobas C Chemistry Analyzer (Roche Diagnostics, Indianapolis, IN) or a Roche/Hitachi Modular P Chemistry Analyzer. HbA1c was measured on a Tosoh Automated Analyzer HLC-723G8 (Tosoh Medics, Inc., San Francisco, CA) or a Tosoh G7 Automated HPLC Analyzer.\u003c/p\u003e\n\u003cp\u003eThe BMD of the lumbar spine was an outcome variable. The spine scans were acquired on Hologic Discovery model A densitometers (Hologic, Inc., Bedford, Massachusetts), using software version Apex 3.2. The radiation exposure from DXA for the spine scan is extremely low at less than 20 uSv. All scans in the \u0026ldquo;DXXSPN_G; DXXSPN_H; DXXSPN_I; DXXSPN_J\u0026rdquo; file were analyzed with Hologic APEX version 4.0 software.\u003c/p\u003e\n\u003cp\u003eThe following data was confounding variables. Age, gender, race, family income, poverty rate, educational level, smoking at least 100 cigarettes in life, active entertainment activities, body mass index (BMI), and other information were obtained by self-reporting. At the same time, in the standardized biochemical test, data such as serum sodium, serum potassium, serum phosphorus, alkaline phosphatase, serum uric acid, blood urea nitrogen, serum creatinine, total protein, total cholesterol, and serum calcium was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong id=\"isPasted\"\u003eStatistical method\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR version 3.4.3 software package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://\" target=\"_blank\"\u003ewww.R-project.org\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) and EmpowerStats (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://\" target=\"_blank\"\u003ewww.empowerstats.com\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) were used. If the P-value is less than 0.05, the difference is statistically significant. The multivariable logistic regression model was used to evaluate the relationship between the status and duration of T2DM, serum glucose, and HbA1c and BMD of the lumbar spine. We built 3 models. In Model 1, covariates were not adjusted; in the Model 2, age, gender and race were adjusted; and in the Model 3, all the covariates were adjusted. At the same time, according to gender, T2DM status,duration, serum glucose, and HbA1c, the subgroup analysis was made. The smooth curve fitting was used to explore the non-linear relationship. We further used the two-segment linear regression model to calculate the inflection points. Finally, we further made the subgroup analysis according to the relationship between serum glucose and HbA1c and BMD of the lumbar spine in different genders and races. We completed the curve fitting.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003cp\u003e\u003cstrong\u003eThe Demographic of Cohort with and without Type 2 Diabetes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, finally, 5,329 people met the standard, including 4,639 non-diabetes patients and 690 diabetes patients. Compared with non-diabetes patients, T2DM patients were older(P\u0026lt;0.001). Their BMI and LSBMD were higher (P\u0026lt;0.001). Adults suffering from T2DM had few entertainment activities and low family income, poverty rate, and education level. Among them, differences between the two groups were significant in alkaline phosphatase, total cholesterol, blood urea nitrogen, serum sodium, serum potassium, serum calcium, blood glucose, and HbA1c in the standard serum biochemical test (P\u0026lt;0.001).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eWeighted Characteristics of Study Sample with and without Type 2 Diabetes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType 2 Diabetes(690)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-Diabetes(4639)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value*\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.76 \u0026plusmn; 5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.07 \u0026plusmn; 5.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e360 (52.17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2257 (48.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e330 (47.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2382 (51.35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (18.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e637 (13.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (10.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e494 (10.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174 (25.22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1638 (35.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e186 (26.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1014 (21.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther Race\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e126 (18.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e856 (18.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.37 \u0026plusmn; 7.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.16 \u0026plusmn; 6.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.88 \u0026plusmn; 8.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e/\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than 9th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79 (11.45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e356 (7.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9-11th grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (15.94%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e571 (12.31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152 (22.03%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1025 (22.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSome college or AA degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e219 (31.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1358 (29.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCollege graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e130 (18.84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1329 (28.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRatio of family income to poverty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.36 \u0026plusmn; 1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.78 \u0026plusmn; 1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVigorous Activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103 (14.93%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1087 (23.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e587 (85.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3552 (76.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoked\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e308 (44.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1967 (42.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e382 (55.36%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2672 (57.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStandard Biochemical Examination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.94 \u0026plusmn; 2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.58 \u0026plusmn; 0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.35 \u0026plusmn; 4.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.38 \u0026plusmn; 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlkaline Phosphatase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.02 \u0026plusmn; 26.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.98 \u0026plusmn; 23.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood Urea Nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.26 \u0026plusmn; 2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.69 \u0026plusmn; 1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum Cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.90 \u0026plusmn; 1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.24 \u0026plusmn; 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum Creatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.79 \u0026plusmn; 84.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.09 \u0026plusmn; 27.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhosphorus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20 \u0026plusmn; 0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19 \u0026plusmn; 0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUric Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e324.77 \u0026plusmn; 89.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e318.51 \u0026plusmn; 83.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSodium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138.40 \u0026plusmn; 2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139.41 \u0026plusmn; 2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePotassium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.04 \u0026plusmn; 0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.95 \u0026plusmn; 0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Proten\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.79 \u0026plusmn; 5.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.46 \u0026plusmn; 4.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Calcium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.33 \u0026plusmn; 0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLumbar Spine BMD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05 \u0026plusmn; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02 \u0026plusmn; 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eResults in the table: mean + SD / N (%)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eP value *: if it is a continuous variable, it shall be obtained by Kruskal Wallis rank sum test. If the theoretical number of counting variables is less than 10, it shall be obtained by Fisher exact probability test.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship between the status and duration of T2DM and lumbar spine BMD\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAs shown in Table 2, we finally built three models. Among them, Model 1: \u0026beta;\u0026thinsp;=\u0026thinsp;0.039, 95% CI: 0.025-0.054, P\u0026lt;0.00001; Model 2 : \u0026beta;\u0026thinsp;=\u0026thinsp;0.043, 95% CI: 0.029-0.057, P\u0026lt;0.00001; and Model 3 (full-adjusted model): \u0026beta;\u0026thinsp;=\u0026thinsp;0.023, 95% CI: 0.004-0.041, P=0.01829. We can know that they were all positively correlated.\u003c/p\u003e\n \u003ctable border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 2\u003c/p\u003e\n \u003cp\u003eAssociations Between the status of T2DM and Lumbar Spinal Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eExposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eNon-adjusted Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eAdjust Model I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eAdjust Model II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eNon-Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eType 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e0.039 (0.025, 0.054) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.043 (0.029, 0.057) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.023 (0.004, 0.041) 0.01829\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eMale with Non-Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eMale with Type 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e0.050 (0.030, 0.070) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.045 (0.025, 0.065) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.015 (-0.013, 0.042) 0.29783\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eFamale with Non-Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003eFamale with Type 2 Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\"\u003e\n \u003cp\u003e0.027 (0.007, 0.047) 0.00770\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.038 (0.019, 0.058) 0.00009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24%\"\u003e\n \u003cp\u003e0.032 (0.007, 0.057) 0.01349\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"24%\"\u003eData in the table: \u0026beta; ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable: Type 2 Diabetes\u003cp\u003eNon-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI;\u0026nbsp; Duration;Vigorous Activities; Smoking; HbA1c; Serum glucose;Alkaline Phosphatase; Blood Urea Nitrogen; Serum Cholesterol; Serum Creatinine; Phosphorus;Uric Acid; Sodium; Potassium; Total Proten; Total Calcium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAccording to the subgroup stratified by gender, we had the following further findings. For men suffering from diabetes, Model 1: \u0026beta;\u0026thinsp;=\u0026thinsp;0.050, 95% CI: 0.030-0.070, P\u0026lt;0.00001; Model 2: \u0026beta;\u0026thinsp;=\u0026thinsp;0.045 95% CI: 0.025-0.065, P\u0026lt;0.00001; and Model 3: \u0026beta;\u0026thinsp;=\u0026thinsp;0.015 95% CI:-0.013-0.042, P=0.29783. For women suffering from diabetes, Model 1: \u0026beta;\u0026thinsp;=\u0026thinsp;0.027, 95% CI: 0.007-0.047, P=0.0077; Model 2: \u0026beta;\u0026thinsp;=\u0026thinsp;0.038, 95% CI: 0.019-0.058, P=0.00009; and Model 3: \u0026beta;\u0026thinsp;=\u0026thinsp;0.032, 95% CI: 0.007-0.057, P=0.01349. In summary, the positive correlation between the two was relatively stable.\u003c/p\u003e\n \u003cp\u003eHowever, as shown in Table 3, there was no significant association between disease duration of T2DM and LSBMD in both genders in all three models (in the Model 3, for males: \u0026beta;\u0026thinsp;=\u0026thinsp;0.001, 95% CI:-0.0015\u0026ndash;0.0035, P=0.433215; for females: \u0026beta;= -0.0018, 95% CI: -0.0037\u0026ndash;0.0001,P=0.061801).\u003c/p\u003e\n \u003ctable border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 3\u003c/p\u003e\n \u003cp\u003eAssociations Between T2DM Duration (Year) and Lumbar Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8%\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003eNon-adjusted Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003eAdjust Model I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003eAdjust Model II\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0003 (-0.0018, 0.0013) 0.742754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0004 (-0.0019, 0.0011) 0.613685\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0007 (-0.0022, 0.0008) 0.363552\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8%\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e0.0010 (-0.0015, 0.0035) 0.432817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e0.0003 (-0.0021, 0.0028) 0.784566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e0.0010 (-0.0015, 0.0035) 0.433215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8%\"\u003e\n \u003cp\u003eFamale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0013 (-0.0032, 0.0006) 0.197111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0011 (-0.0029, 0.0007) 0.226405\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\"\u003e\n \u003cp\u003e-0.0018 (-0.0037, 0.0001) 0.061801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" width=\"8%\"\u003eData in the table: \u0026beta; ( 95%CI) Pvalue; Outcome variable: lumbar spine BMD; Exposure variable: Duration\u003cp\u003eNon-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Vigorous Activities; Smoking; HbA1c; Serum glucose; Alkaline Phosphatase; Blood Urea Nitrogen; Serum Cholesterol; Serum Creatinine; Phosphorus; Uric Acid; Sodium; Potassium; Total Proten; Total Calcium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between serum glucose and lumbar spine BMD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, we built 3 models. Among them, Model 1: \u0026beta;\u0026thinsp;=\u0026thinsp;0.004, 95% CI: 0.002-0.005,P=0.00029; Model 2: \u0026beta;\u0026thinsp;=\u0026thinsp;0.005, 95%CI: 0.003-0.006,P=\u0026lt;0.00001; and Model 3: \u0026beta;\u0026thinsp;=\u0026thinsp;0.004, 95%CI: 0.000-0.007,P=0.02742.We found that there seems to be a slightly linear relationship. We further explored the relationship between the quartile of serum glucose and BMD of the lumbar spine. Finally,We found that they did not have a linear correlation(Model 1:P for trend= 0.734, Model 2:P for trend= 0.092, and Model 3:P for trend= 0.909). We further used the smooth curve fitting method to directly find that they had the relationship of a U-shaped curve (Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). According to the saturation effect and threshold effect analysis, the inflection point was 7.77 mmol/L and the log-likelihood ratio P=0.031༜0.05 (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). It indicated that the curvilinear relationship was established. The subgroups of different genders and races were analyzed. According to the smooth curve fitting, the serum glucose of male ,non-Hispanic whites, Spanish, and other races had a line relationship with the BMD of the lumbar spine. The serum glucose of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. (Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociations Between Serum Glucose (mmol/L) and Lumbar Spinal Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExposure\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-adjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust II\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum Glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004 (0.002, 0.005) 0.00029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.005 (0.003, 0.006) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004 (0.000, 0.007) 0.02742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSerum Glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003 (-0.009, 0.015) 0.61733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007 (-0.004, 0.019) 0.21283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.011 (-0.001, 0.023) 0.06510\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.005 (-0.017, 0.006) 0.36505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.000 (-0.012, 0.012) 0.99526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.000 (-0.012, 0.012) 0.98841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006 (-0.007, 0.018) 0.37293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.014 (0.002, 0.026) 0.02401\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003 (-0.011, 0.017) 0.66512\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eData in the table: \u0026beta; ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Serum Glucose (mmol/L)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eNon-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNonlinearity addressing of Serum glucose(mmol/L)and Lumbar spinal Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome:\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; 95%CI P value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e: Fitting model by standard linear regression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004 (0.000, 0.007) 0.0274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel2\u003c/strong\u003e: Fitting model by two-piecewise linear regression Inflection point\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInflection point\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 7.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.001 (-0.007, 0.004) 0.6271\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; 7.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.007 (0.002, 0.011) 0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for log likelyhood rati o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eData in the table: \u0026beta; ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Serum Glucose (mmol/L)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eNon-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between HbA1c and lumbar spine BMD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, we built 3 models. Among them, Model 1: \u0026beta;\u0026thinsp;=\u0026thinsp;0.007, 95% CI: 0.004-0.011,P=0.00018; Model 2: \u0026beta;\u0026thinsp;=\u0026thinsp;0.009, 95% CI: 0.005-0.013,P\u0026lt;0.00001; and Model 3: \u0026beta;\u0026thinsp;=\u0026thinsp;0.001, 95% CI:-0.007-0.008,P=0.87344. We explored the relationship between the quartile of HbA1c and BMD of the lumbar spine. We found that they did not have a linear correlation((Model 1:P for trend= 0.332, Model 2:P for trend= 0.843, and Model 3:P for trend= 0.016 ). We further used the smooth curve fitting method to directly find that they had the relationship of a U-shaped curve (Figure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). According to the saturation effect and threshold effect analysis, the inflection point was 5.4% and the log-likelihood ratio P༜0.001 (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). It indicated that the Curve relation was established. We further made the subgroup analysis with gender and race. According to the smooth curve fitting, HbA1c of male,non-Hispanic whites and other Spanish had a line relationship with the BMD of the lumbar spine. The HbA1c of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine. (Figure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAssociations Between Glycohemoglobin (%) and Lumbar Spinal Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eExposure\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-adjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust I\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjust II\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.007 (0.004, 0.011) 0.00018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009 (0.005, 0.013) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001 (-0.007, 0.008) 0.87344\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.029 (-0.040, -0.018) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.023 (-0.034, -0.011) 0.00008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.020 (-0.031, -0.008) 0.00081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.031 (-0.044, -0.019) \u0026lt;0.00001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.024 (-0.037, -0.012) 0.00013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.020 (-0.033, -0.007) 0.00328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.006 (-0.019, 0.007) 0.34641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.001 (-0.014, 0.012) 0.90267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.018 (-0.034, -0.002) 0.02599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for trend\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eData in the table: \u0026beta; ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Glycohemoglobin (%);Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eNonlinearity addressing of Glycohemoglobin (%) and Lumbar Spinal Bone Mineral Density (g/cm\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOutcome:\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; 95%CI P value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel 1\u003c/strong\u003e: Fitting model by standard linear regression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.001 (-0.007, 0.008) 0.8734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel2\u003c/strong\u003e: Fitting model by two-piecewise linear regression Inflection point\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInflection point\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.039 (-0.064, -0.014) 0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; 5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006 (-0.002, 0.015) 0.1374\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP for log likelyhood ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eData in the table: \u0026beta; ( 95%CI) P-value; Outcome variable: lumbar spine BMD; Exposure variable:Glycohemoglobin (%); Non-adjusted model adjust for: None; Adjust I model adjust for: Age; Gender; Race ;Adjust II model adjust for: Age; Gender; Race; Education; Ratio; BMI; Duration;Vigorous Activities; Smoking; HbA1c;Serum glucose;Alkaline Phosphatase;Blood Urea Nitrogen;Serum Cholesterol;Serum Creatinine ;Phosphorus;Uric Acid;Sodium;Potassium;Total Proten;Total Calcium\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe morbidity of diabetes has the trend of increasing around the world. 422 million people suffer from diabetes worldwide. 90% of them suffer from T2DM, which is characterized by insulin resistance. T1DM decreases. It is mainly characterized by insulin deficiency. Children and teenagers are the main crowds of diabetes. Diabetes patients often have chronic complications of the cardiovascular system, eyes, kidneys, nervous system, and other systems. In particular, bone strength is also impaired[\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, up to now, researchers do not know the correlation between the fluctuation of serum glucose and the content of HbA1c and BMD.\u003c/p\u003e \u003cp\u003eIn this study, the relationship between T2DM, serum glucose, and HbA1c and BMD of the lumbar spine was explored. In the study, we found that compared with non-T2DM patients T2DM patients had a higher BMD of the lumbar spine, which was positively correlated. Many studies proved that T1DM patients had a lower BMD compared to normal people at the same age and T2DM patients had a normal or higher BMD [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our study also provided evidence for the conclusion, perhaps because T2DM patients had insulin resistance. Insulin is a kind of synthetic hormone. Too much hormone in their body promoted the increase of bone metabolism and synthesis, so the BMD is higher. Some researchers believed that BMD was positively correlated to BMI. We can believe that the increase of BMD is a physiological phenomenon to adapt to the current physical load [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, the risk of fracture of T1DM or T2DM patients is higher than that of normal people [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Most T2DM patients are fat. However, the high BMD caused by obesity may not necessarily provide better protection for fracture. There may be a BMI threshold value, beyond which the bones cannot adapt any more. Therefore, the special parts of the body (such as wrist joints, humerus, etc.) may have a fracture.\u003c/p\u003e \u003cp\u003eAccording to this study, blood glucose and HbA1c have a non-linear relationship with BMD of the lumbar spine. According to the smooth curve effect, we found that they had a relationship of a U-shaped curve. Further, according to the saturation effect analysis, we found that the test effect value of the log-likelihood ratio of the two curves was 0.031 and less than 0.001, respectively. The inflection point of the two curves was 7.77mmol/L and 5.4%, respectively. In a Chinese study, Xu et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] separated monocytes from the marrow of C57BL/6 mice. When the combination of hyperglycemia and hyperinsulinemia was simulated, the osteoclast differentiation and expression of marker genes were down-regulated. Finally, the BMD became higher. However, Jia et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] found in their study that BMD and BMC of the T2DM group were lower than those of the normal group. Our study suggested that blood sugar content and BMD of the lumbar spine had a curvilinear relationship. Besides, when the blood sugar content was 7.77mmol/L, the BMD of the lumbar spine was the lowest. In our study, we further analyzed subgroups of different genders and races. According to the smooth curve fitting, the blood sugar content of male non-Hispanic whites, Spanish, and other races had a line relationship with the BMD of the lumbar spine. The blood sugar content of female non-Hispanic black people and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine.\u003c/p\u003e \u003cp\u003eHbAlc reflects the control of average blood glucose in the last 2-3 months and is not affected by glycometabolism and eating[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The higher HbA1c is, the poorer the control of blood glucose is. At present, many scholars have different opinions on the correlation between HbA1c and BMD. Guo et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] found that when HbA1c was greater than 8.0% the BMD of the neck of the femur significantly decreased. However, Majima et al.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] believed that the BMD of the distal radius of men and women and that of the neck of the femur of women gradually decreased with the increase of HbA1c. Some researchers even found that the BMD and HbA1c had no clear relationship[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, in our study, we found that HbA1c and BMD of the lumbar spine had a curvilinear relationship. Besides, when HbA1c was 5.4%, BMD of the lumbar spine was the lowest. Gender and race were used for further subgroup analysis and smooth curve fitting. We found that the content of HbA1c of male non-Hispanic whites and other Spanish had a line relationship with the BMD of the lumbar spine. The content of HbA1c of female non-Hispanic black people, other Spanish, and Mexican Americans had the relationship of a U-shaped curve with the BMD of the lumbar spine.\u003c/p\u003e"},{"header":"Limitation","content":"\u003cp\u003eHowever, our study also has the following limitations. First, the crowds suffering from diabetes were defined by the self-reporting of diabetes, which caused a big bias. Second, this study is a cross-sectional study. The above conclusion only shows that they are correlated, but they do not have a causal relationship. Finally, in our study, only some covariates were included, As far as I know, BMD is used as the outcome variable. We only selected lumbar BMD, including hip joint BMD and rib BMD. However, in other year cycles, hip joint BMD has some and some do not. The data of bone turnover markers are very old. There are cycles, but not later. The fracture data only passed the questionnaire and was not detailed. We can only hope that the next researcher will continue to study and make more detailed results. Such as whether there is a correlation between the use of antidiabetic drugs and lumbar spine BMD in diabetic patients. If possible, all the confounding factors should be included.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe BMD of the lumbar spine of middle-aged people suffering from T2DM was significantly higher than that of people not suffering from diabetes. Generally speaking, blood glucose and level of HbA1c had a curvilinear relationship with BMD. The curve was U-shaped (The inflection point was 7.77mmol/L and 5.4%). The blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in female non-Hispanic black people and Mexican Americans, they had a relationship of a U-shaped curve with the BMD of the lumbar spine.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eT2DM：Type 2 diabetes mellitus；LSBDN：Lumbar spinal bone mineral density；NHANES; National Health and Nutrition EXamination Survey; HbA1c: Glycosylated hemoglobin; OR: Odds ratio; Cl: Confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBL performed the data analysis. BL and JSL wrote the manuscript. JSL,JPP,HZ and CLZ contributed to the manuscript revise. BL, JSL and CLZ contributed to literature search and data extraction. BL, CLZ and ZJW conceived and designed the study. All authors have read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by the Department of Science Technology of Shandong Province for Key Technology Research and Development Program of Shandong（CN）（NO. 2018GSF118080）and Qingdao Municipal Science and Technology Bureau for demotic science ar technology program（NO. 19-6-1-16-nsh）\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the staff and participants of the NHANES study for their valuable contributions\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe National Center for health statistics ethical review board approved all NHANES protocols, and written informed consent was obtained from all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAmerican Diabetes A: \u003cstrong\u003eDiagnosis and classification of diabetes mellitus\u003c/strong\u003e. \u003cem\u003eDiabetes Care\u0026nbsp;\u003c/em\u003e2012, \u003cstrong\u003e35 Suppl 1\u003c/strong\u003e:S64-71.\u003c/li\u003e\n \u003cli\u003eGe B, Lu S, Lei S: \u003cstrong\u003eThe obesity indices mediate the relationships of blood lipids and bone mineral density in Chinese elders\u003c/strong\u003e. \u003cem\u003eMolecular and cellular probes\u0026nbsp;\u003c/em\u003e2021, \u003cstrong\u003e56\u003c/strong\u003e:101705.\u003c/li\u003e\n \u003cli\u003eJia X, Liu L, Wang R, Liu X, 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\u003cstrong\u003e105\u003c/strong\u003e:18-25.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes mellitus, lumbar spine bone mineral density, serum glucose, HbA1c, cross sectional study, NHANES database","lastPublishedDoi":"10.21203/rs.3.rs-997527/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-997527/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackgrounds:\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eOur purpose is to discuss the relationship among the status and duration of T2DM, serum glucose, glycosylated hemoglobin(HbA1c), and lumbar spine bone mineral density (LSBMD).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eWe selected participants whose age was 40-59 in the NHANES of 2011-2018 for a cross-sectional study. We used the multiple linear regression model to evaluate the status and duration of T2DM, serum glucose, HbA1c, and LSBMD had a linear correlation. We used the smooth curve fitting and threshold effect methods to explore the potential curvilinear relationship and inflection point, further analyzed the subgroups stratified by genders and race and completed the curve fitting.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResult:\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eFinally, 5,329 people met the standard. Finally, we found that the positively correlation between the status of T2DM and the LSBMD, however, the duration of T2DM was\u0026nbsp;not\u0026nbsp;associated\u0026nbsp;with the LSBMD.We further used the smooth curve fitting method to explore. And then we found that blood glucose and level of HbA1c had a curvilinear relationship with the BMD of the lumbar spine in the model. The curve was U-shaped. After the saturation effect and threshold effect analysis, the inflection point was 7.77mmol/L and 5.4%, respectively. According to the further subgroup analysis, we found that the blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in female non-Hispanic black people and Mexican Americans, they had the relationship of a U-shaped curve with the BMD of the lumbar spine.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe BMD of the lumbar spine of middle-aged people suffering from T2DM was significantly higher than those who do not suffer from diabetes. However, the duration of T2DM was\u0026nbsp;not\u0026nbsp;associated\u0026nbsp;with the LSBMD.Generally speaking, blood glucose and level of HbA1c had a curvilinear relationship with the BMD of the lumbar spine. The curve was U-shaped (The inflection point was 7.77mmol/L and 5.4%, respectively). The blood glucose and HbA1c of male non-Hispanic whites were positively correlated to the BMD of the lumbar spine. However, in the female non-Hispanic black people and Mexican Americans, they had the relationship of a U-shaped curve with the BMD of the lumbar spine.\u003c/p\u003e","manuscriptTitle":"Association of T2DM、Serum Glucose、HbA1c With Lumbar Spine Bone Mineral Density in 40-59 years adults: A Cross Sectional Study Based on the 2011-2018 NHANES Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-10-22 18:47:47","doi":"10.21203/rs.3.rs-997527/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-12-17T08:34:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-11-24T11:31:59+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-10-21T07:59:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-10-21T05:58:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-10-20T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-10-20T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2021-10-19T23:19:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0de2ca65-30cc-429c-88ed-7c47bf30661b","owner":[],"postedDate":"October 22nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":8048440,"name":"Orthopedic Surgery"}],"tags":[],"updatedAt":"2021-12-17T13:34:19+00:00","versionOfRecord":[],"versionCreatedAt":"2021-10-22 18:47:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-997527","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-997527","identity":"rs-997527","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}