High Prevalence of Vitamin D Deficiency and Its Association with Early Markers of Kidney Injury in Type 2 Diabetes:A cross-sectional study

High Prevalence of Vitamin D Deficiency and Its Association with Early Markers of Kidney Injury in Type 2 Diabetes:A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article High Prevalence of Vitamin D Deficiency and Its Association with Early Markers of Kidney Injury in Type 2 Diabetes:A cross-sectional study Jianjian Xiang, Nannan Lv, Shanyu Yin, Fei Liu, Feng Liu, Jinsong Kuang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6879564/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Given the unclear role of vitamin D (VD) deficiency in early kidney injury, this study aimed to investigate the association between VD status and diabetic nephropathy (DN) in patients with type 2 diabetes. Methods This cross-sectional study included 909 patients with type 2 diabetes mellitus who received treatment at the Department of Endocrinology and Metabolism of the Fourth People’s Hospital of Shenyang between July and December 2022. Participants were grouped according to serum 25-hydroxyvitamin D [25(OH)D] levels: <10, 10–20, 20–30, and ≥ 30 ng/mL. Clinical data, including blood pressure, body mass index, waist circumference, fasting blood glucose, lipid profiles, glycated hemoglobin (HbA 1c ), C-reactive protein, and urinary albumin-to-creatinine ratio (UACR), were collected. DN was defined based on UACR levels and estimated glomerular filtration rate (eGFR) after excluding other causes of kidney disease. Associations between VD levels and clinical parameters were assessed using linear and logistic regression analyses. Results The prevalence of VD deficiency (< 20 ng/mL) among patients with type 2 diabetes was 81.7%, with 97% exhibiting insufficiency (< 30 ng/mL) and a mean VD level of 14 ± 6.9 ng/mL. Simple linear regression analysis revealed a correlation of VD levels with age, uric acid, and urinary albumin-to-creatinine ratio (P < 0.05). Furthermore, patient stratification by VD levels revealed significant differences in age and uric acid levels among the groups (P < 0.05). Additionally, grouping based on albumin-to-creatinine ratio exhibited significant differences in VD levels (P < 0.05). Conclusions The prevalence of VD deficiency is extremely high among patients with type 2 diabetes and serves as an early indicator of kidney disease, highlighting the need for early screening and potential intervention. Health sciences/Endocrinology/Endocrine system and metabolic diseases Health sciences/Nephrology/Kidney diseases/Chronic kidney disease Diabetic nephropathy New therapeutic targets Type 2 diabetes Vitamin D Figures Figure 1 Figure 2 Figure 3 Background Vitamin D (VD) is a crucial hormone not only for regulating calcium and phosphorus metabolism but also for its recently discovered association with various chronic diseases, including skeletal disorders. VD deficiency is directly linked to rickets, osteoporosis, and an increased risk of fractures. Beyond bone health, VD plays a role in metabolic diseases, such as diabetes, where it influences glucose metabolism by promoting insulin secretion and enhancing insulin sensitivity [ 1 – 4 ]. Observational studies suggest that individuals with VD deficiency exhibit a 30–50% higher risk of developing type 2 diabetes mellitus [ 5 ]. Additionally, low VD levels are inversely associated with obesity and metabolic syndrome, possibly due to their regulatory effects on adipose tissue inflammation [ 6 ]. VD deficiency has also been linked to hypertension, atherosclerosis, and heart failure, though interventional studies have yielded inconclusive results [ 7 , 8 ]. Emerging evidence indicates the potential association between VD deficiency and autoimmune diseases (e.g., multiple sclerosis) as well as certain pulmonary conditions (e.g., inflammatory lung diseases and impaired lung function) [ 9 – 11 ]. Epidemiological studies further suggest that low VD levels may elevate the risk of colorectal and breast cancer [ 12 , 13 ], though a definitive causal relationship remains unconfirmed. Globally, diabetes affects approximately 537 million adults, with China alone accounting for 141 million cases—the highest number worldwide [ 14 ]. As the ninth leading cause of death globally, diabetes contributes to 6.7 million annual deaths, over half of which result from cardiovascular complications. In China, direct medical expenses for diabetes constitute 13% of total health expenditures, amounting to roughly USD 25 billion per year [ 14 , 15 ]. Diabetic kidney disease (DKD), a major microvascular complication of diabetes, contributes to 40–50% of end-stage renal disease (ESRD) cases. Clinically, DKD is classified into five stages based on estimated glomerular filtration rate (eGFR) and urinary protein levels. An estimated 20–40% of patients with diabetes progress to DKD, with over 30 million cases currently reported in China. The 5-year survival rate for patients with DKD is below 50%, and their treatment costs are three to five times higher than those of patients with diabetes alone. Globally, dialysis for DKD-related ESRD incurs annual costs of up to USD 48 billion [ 16 , 17 ]. Cross-sectional studies reveal significantly lower serum VD levels in patients with DKD compared to those without nephropathy [ 18 ]. Small-scale randomized controlled trials (RCTs) suggest that VD supplementation may reduce urinary protein excretion but has limited efficacy in improving eGFR [ 19 ]. Given the global diabetes epidemic and its renal complications, early screening, integrated disease management, and population-level interventions are urgently needed. This raises a critical question: Is VD deficiency a potential risk factor for diabetes and DKD? Based on these considerations, the present study aimed to preliminarily investigate the relationship between VD levels and nephropathy in patients with type 2 diabetes, with the goal of providing evidence to support early targeted interventions and inform the development of novel multi-target therapeutic strategies for DKD. Methods Patient selection criteria and study design The inclusion criteria for this study were: (1) Diagnosis of type 2 diabetes mellitus. (2) Age of 18 years or older. (3) Body mass index (BMI) between 18.5 and 30 kg/m 2 . The exclusion criteria were: (1) Diagnosis of diabetes mellitus other than type 2. (2) Chronic kidney disease (CKD) resulting from non-diabetic nephropathy. (3) Requirement for dialysis. (4) Presence of acute diabetic complications, (5) History of cerebrovascular or cardiovascular disease within the preceding 6 months (6) Presence of malignancy, acute infection, or liver disease. (7) Pregnancy. Type 2 diabetes was diagnosed according to 2014 American Diabetes Association criteria, defined by any of the following: a fasting plasma glucose ≥ 7.0 mmol/L, glycated hemoglobin (HbA 1c ) ≥ 6.5%, or 2-hour plasma glucose level ≥ 11.1 mmol/L following a 75-g oral glucose tolerance test (OGTT) [ 20 ]. This study included 909 patients with type 2 diabetes. Participants were categorized into four groups based on their serum 25-hydroxyvitamin D [25(OH)D] levels: <10 ng/mL, 10–20 ng/mL, 20–30 ng/mL, and ≥ 30 ng/mL. The Medical Ethics Committee of the Fourth People’s Hospital of Shenyang approved this study. All participants provided written informed consent before their enrollment, ensuring adherence to ethical standards and research protocols. Data collection All patients received treatment at the Endocrinology and Metabolism Department of our hospital between July and December 2022. All study-related tests were conducted within the hospital and validated by certified reference laboratories to ensure the accuracy and reliability of the results. During the physical examination, participants wore lightweight clothing and were measured for height without shoes. BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m²). Waist circumference was measured at the midpoint between the lower rib margin and upper iliac crest along the mid-axillary line. The following basic data were collected: sex, age, medical history, medication use, BMI, blood pressure, and waist circumference. Laboratory and imaging evaluations included measurements of serum 25(OH)D, urinary albumin-to-creatinine ratio (UACR), C-reactive protein (CRP), lipid profile (low-density lipoprotein cholesterol [LDL], total cholesterol [TC], high-density lipoprotein cholesterol [HDL], and triglycerides [TG]), serum creatinine (SCr), fasting blood glucose, blood urea nitrogen (BUN), serum uric acid (UA), HbA 1c , albumin-to-creatinine ratio (ACR), and carotid ultrasound findings. Definition of diabetes nephropathy Diabetic nephropathy (DN) was diagnosed based on a persistently elevated UACR and/or a reduced eGFR after excluding other causes of CKD. For this study, participants were further categorized into three groups according to their UACR levels: 30 mg/mmol. 2.4 Statistical analysis Continuous variables are presented as mean ± standard deviation (SD), and categorical variables are expressed as counts and percentages. Comparisons between two groups were performed using the independent samples t-test, Wilcoxon rank-sum test, or chi-square test, as appropriate for the data distribution. Univariate and multivariate linear regression analyses were conducted to assess the relationship between VD levels and other biomarkers. Stepwise logistic regression was used to identify potential influencing factors. Statistical significance was defined as a two-tailed P < 0.05. Results Clinical characteristics of patients The study included 909 patients (Fig. 1 ), with a mean age of 58.26 years ± 10.41 years (Table 1 ) and nearly equal sex distribution (52% males, 48% females). The mean 25(OH)D level was 14.53 ± 6.86 ng/L. Physical examination results showed a mean systolic and diastolic blood pressure of 138.19 ± 17.56 mmHg and 80.72 ± 10.76 mmHg, respectively. The mean BMI was 25.26 ± 3.37 kg/m², with mean waist and hip circumference of 90.6 ± 27.93 cm and 96.34 ± 6.56 cm, respectively. Table 1 Baseline characteristics in the overall cohort. Parameters Overall Cohort (n = 909) Mean SD Gender(%) Male 470(51.71) Female 439(48.29) Age, y 58.26 10.41 25-OH-VitD, ng/mL 14.53 6.86 sBP, mmHg 138.19 17.56 dBP, mmHg 80.72 10.76 Hight, cm 166.55 8.24 Weight, kg 70.31 11.94 BMI, kg/m2 25.26 3.37 Waist circumference, cm 90.60 27.93 Hip circumference, cm 96.34 6.56 glucose 0min, mmol/L 8.15 3.28 glucose 120min, mmol/L 16.30 5.58 HbA1C, % 9.08 2.15 C peptide 0min, µg/L 2.97 27.25 C peptide 120min, µg/L 6.06 53.65 Lp(a), mg/mL 152.35 139.42 TG, mmol/L 2.32 5.95 TC, mmol/L 4.48 1.09 HDL, mmol/L 1.42 5.14 LDL, mmol/L 3.22 10.21 Cr, µmol/L 66.15 22.90 UA, µmol/L 302.94 87.35 BUN, mmol/L 5.86 3.87 Urine CR, mg/g 2055.62 4300.44 Urinary microalbumin, mg/dL 68.50 360.68 UACR, mg/mmol 23.17 94.66 hs CRP, mg/L 3.04 8.55 sBP :systolic Blood pressure; dBP : diastolic blood pressure; BMI :body mass index; CR :serum creatinine; hs CRP :high-sensitivity c-reactive protein Metabolic parameters revealed a mean fasting glucose level of 8.15 ± 3.28 mmol/L that increased to 16.30 ± 4.58 mmol/L at 120 min during OGTT. The mean HbA 1c value was 9.08 ± 2.15%. C-peptide levels increased from 2.97 ± 27.25 µg/L at baseline to 6.06 ± 53.65 µg/L at 120 min. Additional biochemical measurements included BUN, SCr, UA, TG, and TC levels at 5.86 ± 3.87 mmol/L, 66.15 ± 22.9 µmol/L, 302.94 ± 87.35 µmol/L, 2.32 ± 5.95 mmol/L, and 4.48 ± 1.09 mmol/L, respectively. HDL and LDL were 1.42 ± 5.14 mmol/L and 3.22 ± 10.21 mmol/L, respectively. Lipoprotein (a) averaged at 152.35 ± 139.42 mg/mL. Urinary parameters showed a mean urinary creatinine (UCR) of 2055.62 ± 4300.44 mg/g, urinary microalbumin (UMA) of 68.50 ± 360.68 mg/dL, and UACR of 23.17 ± 94.66 mg/mmol. The mean concentration of high-sensitivity CRP (hs-CRP) was 3.04 ± 8.55 mg/L. 3.2 Clinical and biochemical features associated with 25(OH)D To explore the relationship between 25(OH)D levels and diabetic nephropathy in patients with type 2 diabetes, the analysis compared various indicators, including BMI, blood pressure, glucose tolerance, pancreatic function, HBA 1c , blood lipids, urine microalbumin, UACR, renal function, and hs-CRP across the four 25(OH)D groups. The results of the statistical analyses are presented in Table 2 . Table 2 Baseline clinical/biochemical characteristics across 25-OH-VitD. Clinical Data VD(=30) (n = 24) p-value Gender(%) Male 47.86% 53.29% 54.93% 41.67% 0.31 Female 52.14% 46.71% 45.07% 58.33% Age(mean (SD)), y 56.84(10.84) 58.85(10.32) 58.64(10.08) 61.42(7.57) 0.02 sBP(mean (SD)), mmHg 137.86(17.52) 139.24(17.84) 135.68(16.61) 135.38(16.97) 0.15 dBP(mean (SD)), mmHg 79.81(11.93) 81.36(10.25) 80.6(10.58) 78.25(7.55) 0.17 Hight(mean (SD)), cm 166.15(7.96) 166.95(8.29) 166.42(8.41) 163.67(8.96) 0.19 Weight(mean (SD)), kg 69.85(12.18) 70.52(11.54) 71.34(12.90) 64.88(10.40) 0.067 BMI(mean (SD)), kg/m2 25.24(3.73) 25.22(3.20) 25.62(3.28) 24.15(2.80) 0.23 Waist circumference(mean (SD)), cm 89.16(8.67) 91.61(37.31) 90.36(8.94) 86.91(7.77) 0.63 Hip circumference(mean (SD)), cm 96.02(6.93) 96.53(6.38) 96.58(6.59) 94.46(5.77) 0.37 glucose 0min(mean (SD)),mmol/L 8.37(3.35) 8.1(3.37) 8.13(2.99) 6.74(2.03) 0.14 glucose 120min(mean (SD)),mmol/L 15.99(4.55) 16.43(4.6) 16.64(4.68) 15.07(3.54) 0.26 HbA1C(mean (SD)), % 9.20(2.22) 9.05(2.16) 9.02(1.98) 8.64(2.28) 0.57 C peptide 0min(mean (SD)),µg/L 2.08(1.36) 3.73(37.24) 2.09(1.23) 2.38(1.6) 0.85 C peptide 120min(mean (SD)),µg/L 4.28(3.0) 7.57(73.33) 4.34(2.47) 5.01(2.92) 0.85 Lp(a) (mean (SD)), mg/mL 153.58(133.64) 156.43(140.36) 135.37(135.04) 157.21(198.03) 0.46 TG (mean (SD)), mmol/L 2.81(10.79) 2.11(1.87) 2.16(1.87) 2.26(1.72) 0.48 TC(mean (SD)), mmol/L 4.53(1.34) 4.45(0.96) 4.53(1.05) 4.37(0.83) 0.88 HDL(mean (SD)), mmol/L 1.86(9.66) 1.24(0.25) 1.25(0.28) 1.2(0.25) 0.45 LDL (mean (SD)), mmol/L 2.81(0.93) 2.71(0.70) 5.79(25.68) 2.73(0.60) 0.57 CR (mean (SD)), µmol/L 67.33(32.06) 65.89(18.57) 65.25(16.96) 64.17(14.18) 0.42 UA (mean (SD)), µmol/L 290.51(86.88) 306.41(89.33) 309.99(81.55) 323.92(73.62) 0.04 BUN (mean (SD)), mmol/L 5.67(2.16) 5.99(4.98) 5.75(1.4) 5.97(1.42) 0.73 UACR(mean (SD)), mg/mmol 47.28(152.28) 15.70(62.97) 7.27(18.47) 10.32(21.81) 0.06 hsCRP(mean (SD)),mg/L 2.49(7.35) 3.08(8.27) 3.86(11.34) 3.26(6.72) 0.5 sBP :systolic Blood pressure; dBP : diastolic blood pressure; BMI :body mass index; CR :serum creatinine; hs CRP :high-sensitivity c-reactive protein The results indicated that among the collected patient samples, 97.36% had VD levels < 30 ng/mL, and 81.74% had < 20 ng/mL. Significant intergroup differences were observed in age and UA across the different 25(OH)D groups (P < 0.05). No significant differences were found between the groups for other indicators.However, as shown in Table 3 , if we divided the 25-OH-VitD values into two groups based on 30 ng/ml, we can only observe significant differences in body weight and fasting blood glucose between the two groups (P < 0.05). Table 3 Baseline clinical/biochemical characteristics across 25-OH-VitD(30ng/ml). Clinical Data VD(=30) (n = 24) p-value Gender(%) Male 51.98% 41.67% 0.32 Female 48.02% 58.33% Age(mean (SD)), y 58.18(10.47) 61.42(7.57) 0.13 sBP(mean (SD)), mmHg 138.27(17.58) 135.38(16.97) 0.43 dBP(mean (SD)), mmHg 80.79(10.83) 78.25(7.55) 0.26 Hight(mean (SD)), cm 166.43(8.21) 163.67(8.96) 0.08 Weight(mean (SD)), kg 70.46(11.95) 64.88(10.40) 0.02 BMI(mean (SD)), kg/m2 25.29(3.38) 24.15(2.80) 0.10 Waist circumference(mean (SD)), cm 90.70(28.27) 86.91(7.77) 0.51 Hip circumference(mean (SD)), cm 96.39(6.57) 94.46(5.77) 0.16 glucose 0min(mean (SD)),mmol/L 8.19(3.30) 6.74(2.03) < 0.001 glucose 120min(mean (SD)),mmol/L 16.34(4.60) 15.07(3.54) 0.18 HbA1C(mean (SD)), % 9.09(2.15) 8.64(2.28) 0.31 C peptide 0min(mean (SD)),µg/L 2.98(27.61) 2.38(1.6) 0.91 C peptide 120min(mean (SD)),µg/L 6.09(54.37) 5.01(2.92) 0.92 Lp(a) (mean (SD)), mg/mL 152.22(137.64) 157.21(198.03) 0.86 TG (mean (SD)), mmol/L 2.32(6.03) 2.26(1.72) 0.96 TC(mean (SD)), mmol/L 4.48(1.10) 4.37(0.83) 0.61 HDL(mean (SD)), mmol/L 1.42(5.21) 1.2(0.25) 0.84 LDL (mean (SD)), mmol/L 2.81(0.93) 2.73(0.60) 0.81 CR (mean (SD)), µmol/L 66.20(23.09) 64.17(14.18) 0.67 UA (mean (SD)), µmol/L 302.37(87.66) 323.92(73.62) 0.23 BUN (mean (SD)), mmol/L 5.86(3.91) 5.97(1.42) 0.89 UACR(mean (SD)), mg/mmol 23.52(95.84) 10.32(21.81) 0.50 hsCRP(mean (SD)),mg/L 3.04(8.60) 3.26(6.72) 0.90 sBP :systolic Blood pressure; dBP : diastolic blood pressure; BMI :body mass index; CR :serum creatinine; hs CRP :high-sensitivity c-reactive protein 3.3 Linear regression analysis Linear regression analysis demonstrated that 25(OH)D levels showed a significant correlation with patient age (Fig. 2 A). Clinical laboratory results indicated that VD levels were correlated with several indicators, including blood UA, UMA, UCR, and UACR (Fig. 2 B–E). Multiple linear regression analysis revealed associations between VD levels and age, height, weight, BMI, UA levels, and UACR. 3.4 Stratified assessment of 25(OH)D and signs of renal function impairment The correlation analysis revealed an association between 25(OH)D levels and both UA and UACR. Accordingly, differences in 25(OH)D levels and other clinical parameters were examined across UACR (Table 4 ) and eGFR (Table 5 ) categories. Table 4 Comparison across UACR. Clinical Data UACR(=30) (n = 89) p-value Gender(n) Male 279 138 53 0.10 Female 250 153 36 Age(mean (SD)), y 57.70(10.39) 59.31(10.58) 58.17(9.83) 0.11 sBP(mean (SD)), mmHg 135.38(16.97) 131.00(17.36) 145.74(18.16) < 0.001 dBP(mean (SD)), mmHg 80.27(10.41) 80.61(11.45) 83.76(10.09) 0.02 Hight(mean (SD)), cm 167.17(8.03) 165.37(8.17) 166.78(9.35) 0.01 Weight(mean (SD)), kg 70.86(3.44) 68.81(11.25) 71.96(13.54) 0.03 BMI(mean (SD)), kg/m2 25.27(3.44) 25.10(3.27) 25.71(3.24) 0.33 Waist circumference(mean (SD)), cm 89.24(9.21) 92.84(47.48) 91.31(9.07) 0.20 Hip circumference(mean (SD)), cm 96.30(6.42) 96.20(6.66) 97.03(7.05) 0.56 glucose 0min(mean (SD)),mmol/L 7.88(3.02) 8.55(3.59) 8.40(3.61) 0.02 glucose 120min(mean (SD)),mmol/L 15.88(4.41) 17.07(4.88) 16.33(4.26) < 0.001 HbA1C(mean (SD)), % 8.87(2.18) 9.39(2.04) 9.33(2.26) < 0.001 C peptide 0min(mean (SD)),µg/L 3.65(35.70) 1.92(1.18) 2.31(1.54) 0.67 C peptide 120min(mean (SD)),µg/L 7.64(70.29) 3.73(2.08) 4.35(3.07) 0.58 Lp(a) (mean (SD)), mg/mL 152.56(143.55) 141.38(124.89) 187.01(154.64) 0.03 TG (mean (SD)), mmol/L 2.30(7.52) 2.08(1.92) 3.23(3.63) 0.27 TC(mean (SD)), mmol/L 4.40(0.95) 4.48(1.01) 4.99(1.79) < 0.001 HDL(mean (SD)), mmol/L 1.24(0.27) 1.78(9.08) 1.27(0.32) 0.35 LDL (mean (SD)), mmol/L 3.50(13.35) 2.74(0.74) 3.13(1.18) 0.59 CR (mean (SD)), µmol/L 63.78(16.85) 63.18(17.39) 89.93(45.56) < 0.001 UA (mean (SD)), µmol/L 299.88(81.99) 297.14(90.28) 340.06(99.86) < 0.001 BUN (mean (SD)), mmol/L 5.61(1.48) 5.96(6.30) 7.06(2.93) < 0.001 hsCRP(mean (SD)),mg/L 3.03(9.93) 2.73(5.46) 4.12(7.88) 0.41 sBP :systolic Blood pressure; dBP : diastolic blood pressure; BMI :body mass index; CR :serum creatinine; hs CRP :high-sensitivity c-reactive protein Table 5 Comparison across eGFR. Clinical Data eGFR(=90) (n = 584) p-value Gender(n) Male 124 346 < 0.001 Female 201 238 Age(mean (SD)), y 63.89(7.99) 55.13(10.29) < 0.001 sBP(mean (SD)), mmHg 139.67(18.44) 137.37(17.01) 0.06 dBP(mean (SD)), mmHg 79.01(10.43) 81.67(10.83) < 0.001 Hight(mean (SD)), cm 163.31(7.75) 168.36(7.96) < 0.001 Weight(mean (SD)), kg 64.56(9.98) 73.51(11.74) < 0.001 BMI(mean (SD)), kg/m2 24.17(3.08) 25.87(3.37) < 0.001 Waist circumference(mean (SD)), cm 89.67(45.06) 91.11(9.28) 0.46 Hip circumference(mean (SD)), cm 94.40(5.99) 97.42(6.62) < 0.001 glucose 0min(mean (SD)),mmol/L 7.84(3.35) 8.32(3.23) 0.04 glucose 120min(mean (SD)),mmol/L 16.54(4.81) 16.18(4.44) 0.26 HbA1C(mean (SD)), % 8.90(2.09) 9.18(2.18) 0.06 C peptide 0min(mean (SD)),µg/L 2.02(1.30) 3.50(33.98) 0.44 C peptide 120min(mean (SD)),µg/L 4.42(2.68) 6.98(66.91) 0.49 Lp(a) (mean (SD)), mg/mL 165.30(158.52) 145.15(127.14) 0.04 TG (mean (SD)), mmol/L 6.75(6.12) 5.37(1.32) < 0.001 TC(mean (SD)), mmol/L 4.40(0.95) 4.48(1.01) < 0.001 HDL(mean (SD)), mmol/L 1.26(0.29) 1.50(6.41) 0.49 LDL (mean (SD)), mmol/L 3.49(13.68) 3.07(7.62) 0.55 CR (mean (SD)), µmol/L 77.87(29.79) 59.63(14.29) < 0.001 UA (mean (SD)), µmol/L 309.07(97.42) 299.53(81.09) 0.12 BUN (mean (SD)), mmol/L 6.75(6.12) 5.37(1.32) < 0.001 hsCRP(mean (SD)),mg/L 3.42(10.30) 2.84(7.40) 0.33 sBP :systolic Blood pressure; dBP : diastolic blood pressure; BMI :body mass index; CR :serum creatinine; hs CRP :high-sensitivity c-reactive protein For UACR classification (Table 4 ), patients were divided into three groups: 30 mg/mL. Comparative analysis of VD levels and other clinical parameters across these groups revealed significant variations in multiple measures. These included fasting and 2-hour postprandial blood glucose, HbA 1c , blood pressure, lipid profile (TC and lipoprotein (a)), and BUN levels. Importantly, we observed an inverse relationship between ACR categories and VD levels, with mean VD concentrations decreasing as ACR increased (Fig. 3 A,P = 0.02). Conversely, mean BUN levels showed a progressive increase with higher ACR categories. All observed differences were statistically significant. For eGFR analysis (Table 5 ), patients were stratified using a 90 mL/min/1.73 m² cutoff. Significant between-group differences were observed for VD levels and other clinical parameters. Patients with eGFR <90 mL/min/1.73 m² demonstrated significantly higher BUN(P<0.05) and UA(P = 0.12)levels compared to those with higher eGFR levels. But there was no significant difference in vitamin D levels (Fig. 3 B) between the two groups. Discussion The study included 909 patients with type 2 diabetes, stratified by their 25(OH)D levels. These groups were compared across several parameters, including BMI, blood pressure, glucose tolerance, pancreatic function, HBA 1c , blood lipids, UMA, UACR, renal function, and hs-CRP levels. Significant differences were observed between the groups in age and UA(P < 0.05), whereas no significant differences were found for the other indicators. Simple linear regression analysis showed a correlation between 25(OH)D levels and patient age. Additionally, VD levels were associated with several clinical indicators, including blood UA, UMA, UCR, and UACR. Multiple linear regression analysis further revealed that VD levels were associated with age, height, weight, BMI, UA levels, and UACR. Stratification based on UACR revealed additional differences in 25(OH)D levels. VD insufficiency is typically defined as levels below 30 ng/mL, while deficiency is considered below 20 ng/mL. Our study found a high prevalence of these conditions in type 2 diabetes, with 97.36% exhibiting insufficiency and 81.74% exhibiting deficiency. These findings align with international studies reporting similar high rates. A Saudi Arabian study of 1,200 patients with type 2 diabetes mellitus reported 91.3% prevalence of deficiency (serum 25(OH)D levels < 20 ng/mL) [ 21 ], whereas research from northern India (n = 450) reported 94.6% insufficiency (< 30 ng/mL) and 76.2% deficiency (< 20 ng/mL) [ 22 ]. An Iranian study of 1,266 patients documented 81.29% deficiency prevalence (< 20 ng/mL) [ 23 ]. The findings from the aforementioned studies are consistent with our results, indicating that the prevalence of VD deficiency among patients with type 2 diabetes remains high. Our study further demonstrates that VD deficiency prevalence correlates significantly with established kidney disease markers (UA, CR, and UACR). This finding aligns with multiple observational studies reporting associations between serum 25(OH)D levels and diabetic complications, particularly DN [ 24 , 25 ]. Herrmann et al.’s cohort study [ 26 ] revealed sex-specific differences in VD deficiency (P < 0.05), with an initial 18% higher unadjusted risk of microvascular complications (P = 0.006) that decreased to 11–14% and lost significance after adjustment for HbA 1c , seasonality, or physical activity. Supporting our findings, Han et al. [ 27 ] identified an inverse relationship between serum 25(OH)D levels and hyperuricemia in adults in the United States. Clinical evidence from RCTs [ 28 , 29 ] indicates that paricalcitol, a VD receptor agonist, significantly reduces UACR in patients with type 2 diabetes mellitus, potentially through renin–angiotensin system inhibition and anti-inflammatory effects. These collective findings suggest women exhibit greater susceptibility to VD deficiency, the association with metabolic markers (UA, CR, and UACR) appears particularly strong, and deficient VD levels significantly correlate with elevated CR and UACR, specifically among patients with diabetes and CKD. Pathophysiology may involve VD deficiency, which contributes to hyperuricemia via multiple pathways: inflammatory pathways [ 30 , 31 ], impaired renal excretion [ 32 , 33 ], and oxidative stress mechanisms [ 34 ]. DN represents a significant microvascular complication of diabetes mellitus, affecting 30–40% of patients with diabetes during their lifetime. As a primary cause of ESRD [ 35 ], DN poses substantial global economic consequences. The condition typically manifests through progressive proteinuria and a declining glomerular filtration rate. Considering these clinical and economic impacts, developing strategies to prevent or delay DN progression in early disease stages is essential. Our study approach involved stratifying patients by UACR and eGFR to compare clinical indicators. The results indicate that VD status serves as an important influencing factor alongside conventional parameters like blood glucose and lipid levels. These findings suggest that early VD supplementation could potentially slow DN progression [ 36 , 37 ]. This study has several notable strengths. First, the clinical sample size was substantial, with 909 patients with type 2 diabetes included. The sample provided adequate statistical power (> 80%) in this single-center retrospective study, allowing for the effective detection of associations with medium effect sizes. Second, the study addressed critical clinical questions, focusing on the relationship between VD and DN, particularly early markers of renal injury such as ACR. This focus aligns with current priorities in the prevention and management of diabetic microvascular complications. Third, the analysis incorporated multi-dimensional data. Variables including blood pressure, BMI, blood glucose, blood lipids, and HbA 1c were collected, and statistical adjustment for potential confounders was performed to strengthen the validity of the observed associations between VD and nephropathy-related indicators. Finally, our study has important public health implications. VD deficiency was observed in 97% of patients with type 2 diabetes (mean level, 14 ng/ml), a rate markedly higher than that in the general population, highlighting the need for enhanced VD screening among patients with diabetes. Nevertheless, this study also has some limitations. First, its retrospective design introduces inherent risks of selection and recall biases. Although statistical adjustments were made for confounding factors, residual biases cannot be completely excluded. Second, the study was conducted at a single center in China, which may limit the generalizability of the findings to broader populations. Third, due to its cross-sectional nature, the study cannot establish causality; therefore, prospective cohort studies or RCTs are needed to validate these results. Conclusions In conclusion, this study highlights the severity of VD deficiency in patients with type 2 diabetes and its association with early kidney injury markers, offering valuable insights for clinical screening and future mechanistic investigations. Nevertheless, the observational design poses constraints, underscoring the need for further validation through longitudinal and interventional studies. Abbreviations 25(OH)D 25-hydroxyvitamin D ACR Albumin-to-creatinine ratio BUN Blood urea nitrogen CRP C-reactive protein CKD Chronic kidney disease DKD Diabetic kidney disease ESRD End-stage renal disease HbA 1c Glycated hemoglobin HDL High-density lipoprotein cholesterol LDL Low-density lipoprotein cholesterol OGTT Oral glucose tolerance test RCTs Randomized controlled trials SCr Serum creatinine SD Standard deviation TC Total cholesterol TG Triglycerides UA Serum uric acid UACR Urinary albumin-to-creatinine ratio UMA Urinary microalbumin UCR Urinary creatinine Declarations Human Ethics and Consent to Participate The study was conducted in accordance with the Declaration of Helsinki, and approved by The Medical Ethics Committee of the Fourth People’s Hospital of Shenyang (Approval No. 2021(11)-01). Informed consent was obtained from all subjects involved in the study. Consent for publication All participants (or their legal guardians) provided written informed consent for the publication of anonymized data obtained in this study. Identifying details (e.g., names, hospital IDs, dates of birth) have been removed to protect participant privacy. Clinical trial number Not applicable. Availability of data and materials De-identified participant data are available upon reasonable request to the corresponding author. Competing interests The authors declare that they have no competing interests. Funding The authors declare that they received financial support for the research, authorship, and publication of this article. This study was supported by the Scientific and Technical Program of Shenyang (grant number 22-321-33-61) and. Noncommunicable Chronic Diseases-National Science and Technology Major Project (grant number: 2023ZD0508100). Authors' contributions All the authors met the ICMJE criteria for authorship and approved the final version of the manuscript. Individual contributions are as follows. NL: Funding acquisition, Conceptualization, Methodology, Formal Analysis, Writing of the Original Draft. JX: Data curation, Investigation, Validation, and Writing of the original draft. JS: Methodology, Software, Writing, review and editing. SY, FL, and FL: Writing, review, and editing. JK: Supervision Acknowledgments The authors would like to thank the team of investigators, research partners, and operational staff involved in this study. We also extend gratitude to Editage (editage.com/frontiers) for their linguistic assistance during the preparation of this manuscript. References Giustina, A. et al. Consensus Statement on Vitamin D Status Assessment and Supplementation: Whys, Whens, and Hows. Endocr. Rev. 45 (5), 625–654. 10.1210/endrev/bnae009 (2024). Zhao, S. et al. Vitamin D and major chronic diseases. Trends Endocrinol. Metab. 35 (12), 1050–1061. 10.1016/j.tem.2024.04.018 (2024). Dawson-Hughes, B. et al. Intratrial Exposure to Vitamin D and New-Onset Diabetes Among Adults With Prediabetes: A Secondary Analysis From the Vitamin D and Type 2 Diabetes (D2d) Study. Diabetes Care . 43 (12), 2916–2922. 10.2337/dc20-1765 (2020). McKenna, M. J. & Flynn, M. A. T. Preventing Type 2 Diabetes With Vitamin D: Therapy Versus Supplementation. Ann. Intern. Med. 176 (3), 415–416. 10.7326/M23-0220 (2023). Pittas, A. G. et al. Vitamin D Supplementation and Prevention of Type 2 Diabetes. N Engl. J. Med. 381 (6), 520–530. 10.1056/NEJMoa1900906 (2019). Wamberg, L. et al. Expression of vitamin D-metabolizing enzymes in human adipose tissue -- the effect of obesity and diet-induced weight loss. Int. J. Obes. (Lond) . 37 (5), 651–657. 10.1038/ijo.2012.112 (2013). Vimaleswaran, K. S. et al. Association of vitamin D status with arterial blood pressure and hypertension risk: a mendelian randomisation study. Lancet Diabetes Endocrinol. 2 (9), 719–729. 10.1016/S2213- (2014). Zittermann, A. & Pilz, S. Vitamin D and Cardiovascular Disease: An Update. Anticancer Res. 39 (9), 4627–4635. 10.21873/anticanres.13643 (2019). Ascherio, A. et al. Vitamin D as an early predictor of multiple sclerosis activity and progression. JAMA Neurol. 71 (3), 306–314. 10.1001/jamaneurol.2013.5993 (2014). Song, G. G., Bae, S. C. & Lee, Y. H. Association between vitamin D intake and the risk of rheumatoid arthritis: a meta-analysis. Clin. Rheumatol. 31 (12), 1733–1739. 10.1007/s10067-012-2080-7 (2012). Jolliffe, D. A. et al. Vitamin D supplementation to prevent acute respiratory infections: a systematic review and meta-analysis of aggregate data from randomised controlled trials. Lancet Diabetes Endocrinol. 9 (5), 276–292. 10.1016/S2213-8587(21)00051-6 (2021). Emmanouilidou, G. et al. Vitamin D as a chemopreventive agent in colorectal neoplasms. A systematic review and meta-analysis of randomized controlled trials. Pharmacol. Ther. 237 , 108252. 10.1016/j.pharmthera.2022.108252 (2022). Estébanez, N., Gómez-Acebo, I., Palazuelos, C., Llorca, J. & Dierssen-Sotos, T. Vitamin D exposure and Risk of Breast Cancer: a meta-analysis. Sci. Rep. 8 (1), 9039. 10.1038/s41598-018-27297-1 (2018). Magliano, D. J. & Boyko, E. J. IDF Diabetes Atlas 10th edition scientific committee. IDF DIABETES ATLAS [Internet] 10th edn PMID: 35914061 (International Diabetes Federation, 2021). Artime, E., Romera, I., Díaz-Cerezo, S. & Delgado, E. Epidemiology and Economic Burden of Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus in Spain: A Systematic Review. Diabetes Ther. 12 (6), 1631–1659. 10.1007/s13300-021-01060-8 (2021). Li, Y. et al. Temporal trends in prevalence and mortality for chronic kidney disease in China from 1990 to 2019: an analysis of the Global Burden of Disease Study 2019. Clin. Kidney J. 16 (2), 312–321. 10.1093/ckj/sfac 218 (2022). Alicic, R. Z., Rooney, M. T. & Tuttle, K. R. Diabetic Kidney Disease: Challenges, Progress, and Possibilities. Clin. J. Am. Soc. Nephrol. 12 (12), 2032–2045. 10.2215/CJN.114911 16 (2017). Verma, S. et al. Empagliflozin and Cardiovascular Outcomes in Patients With Type 2 Diabetes and Left Ventricular Hypertrophy: A Subanalysis of the EMPA-REG OUTCOME Trial. Diabetes Care . 42 (3), e42–e44. 10.2337/dc18-1959 (2019). Wang, Y., Yang, S., Zhou, Q., Zhang, H. & Yi, B. Effects of Vitamin D Supplementation on Renal Function, Inflammation and Glycemic Control in Patients with Diabetic Nephropathy: a Systematic Review and Meta-Analysis. Kidney Blood Press. Res. 44 (1), 72–87. 10.1159/000498838 (2019). American Diabetes Association. Standards of medical care in diabetes–2014. Diabetes Care . 37 (Suppl 1), S14–80. 10.2337/dc14-S014 (2014). Al-Daghri, N. M. et al. Vitamin D Deficiency and Cardiometabolic Risks: A Juxtaposition of Arab Adolescents and Adults. PLoS One . 10 (7), e0131315. 10.1371/journal.pone.0131315 (2015). Bora, K. & Ruram, A. A. No association of 25-hydroxyvitamin D and parathormone levels with glucose homeostasis in type 2 diabetes - a study from Shillong, Meghalaya. Int. J. Vitam. Nutr. Res. 89 (5–6), 285–292. 10.1024/0300-9831/a000567 (2019). Ghodsi, M. et al. Association of vitamin D receptor gene polymorphism with the occurrence of low bone density, osteopenia, and osteoporosis in patients with type 2 diabetes. J. Diabetes Metab. Disord . 20 (2), 1375–1383. 10.1007/s40200-021-00871-7 (2021). Zhou, C. et al. Relationships of Serum 25-Hydroxyvitamin D Concentrations, Diabetes, Genetic Susceptibility, and New-Onset Chronic Kidney Disease. Diabetes Care . 45 (11), 2518–2525. 10.2337/dc22-1194 (2022). Chen, X. et al. Vitamin D Status, Vitamin D Receptor Polymorphisms, and Risk of Microvascular Complications Among Individuals With Type 2 Diabetes: A Prospective Study. Diabetes Care . 46 (2), 270–277. 10.2337/dc22-0513 (2023). Herrmann, M. et al. Serum 25-Hydroxyvitamin D: A Predictor of Macrovascular and Microvascular Complications in Patients With Type 2 Diabetes. Diabetes Care 1 March . 38 (3), 521–528. 10.2337/dc14-0180 (2015). Han, Y., Han, K., Zhang, Y. & Zeng, X. Serum 25-hydroxyvitamin D might be negatively associated with hyperuricemia in U.S. adults: an analysis of the National Health and Nutrition Examination Survey 2007–2014. J. Endocrinol. Invest. 45 (4), 719–729. 10.1007/s40618-021-01637-x (2022). de Zeeuw, D. et al. Selective vitamin D receptor activation with paricalcitol for reduction of albuminuria in patients with type 2 diabetes (VITAL study): a randomised controlled trial. Lancet 376 (9752), 1543–1551. 10.1016/S0140-6736(10)61032-X (2010). Alborzi, P. et al. Paricalcitol reduces albuminuria and inflammation in chronic kidney disease: a randomized double-blind pilot trial. Hypertension 52 (2), 249–255. 10.1161/HYPERTENSIONAHA.108.113159 (2008). Zhang, Z. et al. 1,25-Dihydroxyvitamin D3 targeting of NF-kappaB suppresses high glucose-induced MCP-1 expression in mesangial cells. Kidney Int. 72 (2), 193–201. 10.1038/sj.ki.5002296 (2007). Dusso, A. S. & Tokumoto, M. Defective renal maintenance of the vitamin D endocrine system impairs vitamin D renoprotection: a downward spiral in kidney disease. Kidney Int. 79 (7), 715–729. 10.1038/ki.2010.543 (2011). Li, Y. C. et al. 1,25-Dihydroxyvitamin D(3) is a negative endocrine regulator of the renin-angiotensin system. J. Clin. Invest. 110 (2), 229–238. 10.1172/JCI15219 (2002). Yuan, W. et al. 1,25-dihydroxyvitamin D3 suppresses renin gene transcription by blocking the activity of the cyclic AMP response element in the renin gene promoter. J. Biol. Chem. 282 (41), 29821–29830. 10.1074/jbc.M705495200 (2007). Bourgonje, A. R. et al. Serum peroxiredoxin-4, a biomarker of oxidative stress, is associated with the development of nephropathy in patients with type 2 diabetes (Zodiac-65). Free Radic Biol. Med. 212 , 186–190. 10.1016/j.freeradbiomed.2023.12.025 (2024). Gupta, S., Dominguez, M. & Golestaneh, L. Diabetic Kidney Disease: An Update. Med. Clin. North. Am. 107 (4), 689–705. 10.1016/j.mcna.2023.03.004 (2023). de Zeeuw, D. et al. Selective vitamin D receptor activation with paricalcitol for reduction of albuminuria in patients with type 2 diabetes (VITAL study): a randomised controlled trial. Lancet 376 (9752), 1543–1551. 10.1016/S0140-6736(10)61032-X (2010). Wang, Y. et al. Vitamin D receptor signaling in podocytes protects against diabetic nephropathy. J. Am. Soc. Nephrol. 23 (12), 1977–1986. 10.1681/ASN.2012040383 (2012). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6879564","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":473698310,"identity":"e9fcfa06-b009-48a3-acec-3eec53895bd8","order_by":0,"name":"Jianjian Xiang","email":"","orcid":"","institution":"The First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jianjian","middleName":"","lastName":"Xiang","suffix":""},{"id":473698311,"identity":"5f9d2a4a-54ad-4018-990e-4e586a8ab084","order_by":1,"name":"Nannan 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cross-sectional study\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6879564/v1/128a5bd13b49ea76e01486e9.png"},{"id":85385182,"identity":"3c5c7469-9fcd-4605-a430-34eadbb8eeb7","added_by":"auto","created_at":"2025-06-25 09:41:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44737,"visible":true,"origin":"","legend":"\u003cp\u003e25-OH-VitD and clinical indicators\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6879564/v1/921aef6090942b5760c4c906.png"},{"id":85385189,"identity":"c4830e8c-88e6-4656-bf20-1bf19f051817","added_by":"auto","created_at":"2025-06-25 09:41:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19203,"visible":true,"origin":"","legend":"\u003cp\u003e25-OH-VitD and signs of renal function impairment\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6879564/v1/e1627ee1955d75fe255b5005.png"},{"id":85848654,"identity":"695014e7-7800-4c1e-8e40-80570341fb8c","added_by":"auto","created_at":"2025-07-02 10:02:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1465165,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6879564/v1/6b874672-0311-4136-8d8f-df0cca2a6196.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"High Prevalence of Vitamin D Deficiency and Its Association with Early Markers of Kidney Injury in Type 2 Diabetes:A cross-sectional study","fulltext":[{"header":"Background","content":"\u003cp\u003eVitamin D (VD) is a crucial hormone not only for regulating calcium and phosphorus metabolism but also for its recently discovered association with various chronic diseases, including skeletal disorders. VD deficiency is directly linked to rickets, osteoporosis, and an increased risk of fractures. Beyond bone health, VD plays a role in metabolic diseases, such as diabetes, where it influences glucose metabolism by promoting insulin secretion and enhancing insulin sensitivity [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Observational studies suggest that individuals with VD deficiency exhibit a 30\u0026ndash;50% higher risk of developing type 2 diabetes mellitus [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, low VD levels are inversely associated with obesity and metabolic syndrome, possibly due to their regulatory effects on adipose tissue inflammation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. VD deficiency has also been linked to hypertension, atherosclerosis, and heart failure, though interventional studies have yielded inconclusive results [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Emerging evidence indicates the potential association between VD deficiency and autoimmune diseases (e.g., multiple sclerosis) as well as certain pulmonary conditions (e.g., inflammatory lung diseases and impaired lung function) [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Epidemiological studies further suggest that low VD levels may elevate the risk of colorectal and breast cancer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], though a definitive causal relationship remains unconfirmed.\u003c/p\u003e \u003cp\u003eGlobally, diabetes affects approximately 537\u0026nbsp;million adults, with China alone accounting for 141\u0026nbsp;million cases\u0026mdash;the highest number worldwide [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. As the ninth leading cause of death globally, diabetes contributes to 6.7\u0026nbsp;million annual deaths, over half of which result from cardiovascular complications. In China, direct medical expenses for diabetes constitute 13% of total health expenditures, amounting to roughly USD 25\u0026nbsp;billion per year [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Diabetic kidney disease (DKD), a major microvascular complication of diabetes, contributes to 40\u0026ndash;50% of end-stage renal disease (ESRD) cases. Clinically, DKD is classified into five stages based on estimated glomerular filtration rate (eGFR) and urinary protein levels. An estimated 20\u0026ndash;40% of patients with diabetes progress to DKD, with over 30\u0026nbsp;million cases currently reported in China. The 5-year survival rate for patients with DKD is below 50%, and their treatment costs are three to five times higher than those of patients with diabetes alone. Globally, dialysis for DKD-related ESRD incurs annual costs of up to USD 48\u0026nbsp;billion [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCross-sectional studies reveal significantly lower serum VD levels in patients with DKD compared to those without nephropathy [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Small-scale randomized controlled trials (RCTs) suggest that VD supplementation may reduce urinary protein excretion but has limited efficacy in improving eGFR [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Given the global diabetes epidemic and its renal complications, early screening, integrated disease management, and population-level interventions are urgently needed. This raises a critical question: Is VD deficiency a potential risk factor for diabetes and DKD? Based on these considerations, the present study aimed to preliminarily investigate the relationship between VD levels and nephropathy in patients with type 2 diabetes, with the goal of providing evidence to support early targeted interventions and inform the development of novel multi-target therapeutic strategies for DKD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection criteria and study design\u003c/h2\u003e \u003cp\u003eThe inclusion criteria for this study were:\u003c/p\u003e \u003cp\u003e(1) Diagnosis of type 2 diabetes mellitus.\u003c/p\u003e \u003cp\u003e(2) Age of 18 years or older.\u003c/p\u003e \u003cp\u003e(3) Body mass index (BMI) between 18.5 and 30 kg/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe exclusion criteria were:\u003c/p\u003e \u003cp\u003e(1) Diagnosis of diabetes mellitus other than type 2.\u003c/p\u003e \u003cp\u003e(2) Chronic kidney disease (CKD) resulting from non-diabetic nephropathy.\u003c/p\u003e \u003cp\u003e(3) Requirement for dialysis.\u003c/p\u003e \u003cp\u003e(4) Presence of acute diabetic complications,\u003c/p\u003e \u003cp\u003e(5) History of cerebrovascular or cardiovascular disease within the preceding 6 months\u003c/p\u003e \u003cp\u003e(6) Presence of malignancy, acute infection, or liver disease.\u003c/p\u003e \u003cp\u003e(7) Pregnancy.\u003c/p\u003e \u003cp\u003eType 2 diabetes was diagnosed according to 2014 American Diabetes Association criteria, defined by any of the following: a fasting plasma glucose\u0026thinsp;\u0026ge;\u0026thinsp;7.0 mmol/L, glycated hemoglobin (HbA\u003csub\u003e1c\u003c/sub\u003e)\u0026thinsp;\u0026ge;\u0026thinsp;6.5%, or 2-hour plasma glucose level\u0026thinsp;\u0026ge;\u0026thinsp;11.1 mmol/L following a 75-g oral glucose tolerance test (OGTT) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study included 909 patients with type 2 diabetes. Participants were categorized into four groups based on their serum 25-hydroxyvitamin D [25(OH)D] levels: \u0026lt;10 ng/mL, 10\u0026ndash;20 ng/mL, 20\u0026ndash;30 ng/mL, and \u0026ge;\u0026thinsp;30 ng/mL.\u003c/p\u003e \u003cp\u003e The Medical Ethics Committee of the Fourth People\u0026rsquo;s Hospital of Shenyang approved this study. All participants provided written informed consent before their enrollment, ensuring adherence to ethical standards and research protocols.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eAll patients received treatment at the Endocrinology and Metabolism Department of our hospital between July and December 2022. All study-related tests were conducted within the hospital and validated by certified reference laboratories to ensure the accuracy and reliability of the results.\u003c/p\u003e \u003cp\u003eDuring the physical examination, participants wore lightweight clothing and were measured for height without shoes. BMI was calculated as weight in kilograms divided by the square of height in meters (kg/m\u0026sup2;). Waist circumference was measured at the midpoint between the lower rib margin and upper iliac crest along the mid-axillary line.\u003c/p\u003e \u003cp\u003eThe following basic data were collected: sex, age, medical history, medication use, BMI, blood pressure, and waist circumference.\u003c/p\u003e \u003cp\u003eLaboratory and imaging evaluations included measurements of serum 25(OH)D, urinary albumin-to-creatinine ratio (UACR), C-reactive protein (CRP), lipid profile (low-density lipoprotein cholesterol [LDL], total cholesterol [TC], high-density lipoprotein cholesterol [HDL], and triglycerides [TG]), serum creatinine (SCr), fasting blood glucose, blood urea nitrogen (BUN), serum uric acid (UA), HbA\u003csub\u003e1c\u003c/sub\u003e, albumin-to-creatinine ratio (ACR), and carotid ultrasound findings.\u003c/p\u003e\n\u003ch3\u003eDefinition of diabetes nephropathy\u003c/h3\u003e\n\u003cp\u003eDiabetic nephropathy (DN) was diagnosed based on a persistently elevated UACR and/or a reduced eGFR after excluding other causes of CKD. For this study, participants were further categorized into three groups according to their UACR levels: \u0026lt;2.5 mg/mmol, 2.5\u0026ndash;30 mg/mmol, and \u0026gt;\u0026thinsp;30 mg/mmol.\u003c/p\u003e\n\u003ch3\u003e2.4 Statistical analysis\u003c/h3\u003e\n\u003cp\u003eContinuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and categorical variables are expressed as counts and percentages. Comparisons between two groups were performed using the independent samples t-test, Wilcoxon rank-sum test, or chi-square test, as appropriate for the data distribution. Univariate and multivariate linear regression analyses were conducted to assess the relationship between VD levels and other biomarkers. Stepwise logistic regression was used to identify potential influencing factors. Statistical significance was defined as a two-tailed P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical characteristics of patients\u003c/h2\u003e \u003cp\u003eThe study included 909 patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with a mean age of 58.26 years\u0026thinsp;\u0026plusmn;\u0026thinsp;10.41 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and nearly equal sex distribution (52% males, 48% females). The mean 25(OH)D level was 14.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.86 ng/L. Physical examination results showed a mean systolic and diastolic blood pressure of 138.19\u0026thinsp;\u0026plusmn;\u0026thinsp;17.56 mmHg and 80.72\u0026thinsp;\u0026plusmn;\u0026thinsp;10.76 mmHg, respectively. The mean BMI was 25.26\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37 kg/m\u0026sup2;, with mean waist and hip circumference of 90.6\u0026thinsp;\u0026plusmn;\u0026thinsp;27.93 cm and 96.34\u0026thinsp;\u0026plusmn;\u0026thinsp;6.56 cm, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics in the overall cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall Cohort\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;909)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e470(51.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e439(48.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25-OH-VitD, ng/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHight, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI, kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 0min, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 120min, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 0min, \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 120min, \u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a), mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e152.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e139.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e302.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e87.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrine CR, mg/g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2055.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4300.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrinary microalbumin, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e68.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e360.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUACR, mg/mmol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs CRP, mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003esBP\u003c/b\u003e:systolic Blood pressure; \u003cb\u003edBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eBMI\u003c/b\u003e:body mass index; \u003cb\u003eCR\u003c/b\u003e:serum creatinine;\u003cb\u003ehs CRP\u003c/b\u003e:high-sensitivity c-reactive protein\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMetabolic parameters revealed a mean fasting glucose level of 8.15\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28 mmol/L that increased to 16.30\u0026thinsp;\u0026plusmn;\u0026thinsp;4.58 mmol/L at 120 min during OGTT. The mean HbA\u003csub\u003e1c\u003c/sub\u003e value was 9.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.15%. C-peptide levels increased from 2.97\u0026thinsp;\u0026plusmn;\u0026thinsp;27.25 \u0026micro;g/L at baseline to 6.06\u0026thinsp;\u0026plusmn;\u0026thinsp;53.65 \u0026micro;g/L at 120 min.\u003c/p\u003e \u003cp\u003eAdditional biochemical measurements included BUN, SCr, UA, TG, and TC levels at 5.86\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87 mmol/L, 66.15\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9 \u0026micro;mol/L, 302.94\u0026thinsp;\u0026plusmn;\u0026thinsp;87.35 \u0026micro;mol/L, 2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;5.95 mmol/L, and 4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09 mmol/L, respectively. HDL and LDL were 1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;5.14 mmol/L and 3.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.21 mmol/L, respectively. Lipoprotein (a) averaged at 152.35\u0026thinsp;\u0026plusmn;\u0026thinsp;139.42 mg/mL.\u003c/p\u003e \u003cp\u003eUrinary parameters showed a mean urinary creatinine (UCR) of 2055.62\u0026thinsp;\u0026plusmn;\u0026thinsp;4300.44 mg/g, urinary microalbumin (UMA) of 68.50\u0026thinsp;\u0026plusmn;\u0026thinsp;360.68 mg/dL, and UACR of 23.17\u0026thinsp;\u0026plusmn;\u0026thinsp;94.66 mg/mmol. The mean concentration of high-sensitivity CRP (hs-CRP) was 3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55 mg/L.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e3.2 Clinical and biochemical features associated with 25(OH)D\u003c/h3\u003e\n\u003cp\u003eTo explore the relationship between 25(OH)D levels and diabetic nephropathy in patients with type 2 diabetes, the analysis compared various indicators, including BMI, blood pressure, glucose tolerance, pancreatic function, HBA\u003csub\u003e1c\u003c/sub\u003e, blood lipids, urine microalbumin, UACR, renal function, and hs-CRP across the four 25(OH)D groups. The results of the statistical analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline clinical/biochemical characteristics across 25-OH-VitD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVD(\u0026lt;10)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;257)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVD(10\u0026ndash;20)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;486)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVD(20\u0026ndash;30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;142)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eVD(\u0026gt;=30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.93%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e41.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.07%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(mean (SD)), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.84(10.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.85(10.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e58.64(10.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e61.42(7.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e137.86(17.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e139.24(17.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135.68(16.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e135.38(16.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.81(11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81.36(10.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.6(10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e78.25(7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHight(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166.15(7.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e166.95(8.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e166.42(8.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163.67(8.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(mean (SD)), kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.85(12.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70.52(11.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71.34(12.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64.88(10.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.067\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(mean (SD)), kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.24(3.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.22(3.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25.62(3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.15(2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e89.16(8.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.61(37.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.36(8.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e86.91(7.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.02(6.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96.53(6.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.58(6.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e94.46(5.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 0min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.37(3.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.1(3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.13(2.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.74(2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 120min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.99(4.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.43(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.64(4.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.07(3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C(mean (SD)), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.20(2.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.05(2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.02(1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.64(2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 0min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.08(1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.73(37.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.09(1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.38(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 120min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.28(3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.57(73.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.34(2.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.01(2.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (mean (SD)), mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e153.58(133.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e156.43(140.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e135.37(135.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e157.21(198.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.81(10.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.11(1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.16(1.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.26(1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.53(1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.45(0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.53(1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.37(0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.86(9.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.24(0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.25(0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.2(0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.81(0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.71(0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.79(25.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.73(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e67.33(32.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.89(18.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e65.25(16.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e64.17(14.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e290.51(86.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e306.41(89.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e309.99(81.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e323.92(73.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.67(2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.99(4.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.75(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.97(1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUACR(mean (SD)), mg/mmol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.28(152.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.70(62.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.27(18.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10.32(21.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP(mean (SD)),mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.49(7.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.08(8.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.86(11.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.26(6.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003esBP\u003c/b\u003e:systolic Blood pressure; \u003cb\u003edBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eBMI\u003c/b\u003e:body mass index; \u003cb\u003eCR\u003c/b\u003e:serum creatinine;\u003cb\u003ehs CRP\u003c/b\u003e:high-sensitivity c-reactive protein\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results indicated that among the collected patient samples, 97.36% had VD levels\u0026thinsp;\u0026lt;\u0026thinsp;30 ng/mL, and 81.74% had\u0026thinsp;\u0026lt;\u0026thinsp;20 ng/mL. Significant intergroup differences were observed in age and UA across the different 25(OH)D groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No significant differences were found between the groups for other indicators.However, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, if we divided the 25-OH-VitD values into two groups based on 30 ng/ml, we can only observe significant differences in body weight and fasting blood glucose between the two groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline clinical/biochemical characteristics across 25-OH-VitD(30ng/ml).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVD(\u0026lt;30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;885)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVD(\u0026gt;=30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e51.98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(mean (SD)), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.18(10.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e61.42(7.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138.27(17.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135.38(16.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.79(10.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e78.25(7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHight(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e166.43(8.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e163.67(8.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(mean (SD)), kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.46(11.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.88(10.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(mean (SD)), kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.29(3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.15(2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.70(28.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86.91(7.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.39(6.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94.46(5.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 0min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.19(3.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6.74(2.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 120min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.34(4.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.07(3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C(mean (SD)), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.09(2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.64(2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 0min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.98(27.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.38(1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 120min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.09(54.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.01(2.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (mean (SD)), mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e152.22(137.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e157.21(198.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.32(6.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.26(1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.48(1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.37(0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.42(5.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.2(0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.81(0.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.73(0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66.20(23.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64.17(14.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e302.37(87.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e323.92(73.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.86(3.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.97(1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUACR(mean (SD)), mg/mmol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.52(95.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.32(21.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP(mean (SD)),mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.04(8.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.26(6.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003esBP\u003c/b\u003e:systolic Blood pressure; \u003cb\u003edBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eBMI\u003c/b\u003e:body mass index; \u003cb\u003eCR\u003c/b\u003e:serum creatinine;\u003cb\u003ehs CRP\u003c/b\u003e:high-sensitivity c-reactive protein\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e3.3 Linear regression analysis\u003c/h3\u003e\n\u003cp\u003eLinear regression analysis demonstrated that 25(OH)D levels showed a significant correlation with patient age (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Clinical laboratory results indicated that VD levels were correlated with several indicators, including blood UA, UMA, UCR, and UACR (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u0026ndash;E). Multiple linear regression analysis revealed associations between VD levels and age, height, weight, BMI, UA levels, and UACR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Stratified assessment of 25(OH)D and signs of renal function impairment\u003c/h2\u003e \u003cp\u003eThe correlation analysis revealed an association between 25(OH)D levels and both UA and UACR. Accordingly, differences in 25(OH)D levels and other clinical parameters were examined across UACR (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and eGFR (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) categories.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison across UACR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUACR(\u0026lt;2.5)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;529)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUACR\u003c/p\u003e \u003cp\u003e(2.5\u0026ndash;30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;291)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUACR(\u0026gt;=30)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender(n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(mean (SD)), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.70(10.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.31(10.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.17(9.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135.38(16.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131.00(17.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e145.74(18.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.27(10.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.61(11.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83.76(10.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHight(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167.17(8.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165.37(8.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e166.78(9.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(mean (SD)), kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.86(3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.81(11.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.96(13.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(mean (SD)), kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.27(3.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.10(3.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.71(3.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.24(9.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.84(47.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.31(9.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.30(6.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.20(6.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.03(7.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 0min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.88(3.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.55(3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.40(3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 120min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.88(4.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.07(4.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.33(4.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C(mean (SD)), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.87(2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.39(2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.33(2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 0min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.65(35.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.92(1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.31(1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 120min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.64(70.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.73(2.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.35(3.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (mean (SD)), mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152.56(143.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141.38(124.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e187.01(154.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.30(7.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.08(1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.23(3.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.40(0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.48(1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.99(1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.24(0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.78(9.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27(0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.50(13.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.74(0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.13(1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.78(16.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.18(17.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.93(45.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e299.88(81.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297.14(90.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e340.06(99.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.61(1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.96(6.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.06(2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP(mean (SD)),mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.03(9.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.73(5.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.12(7.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cb\u003esBP\u003c/b\u003e:systolic Blood pressure; \u003cb\u003edBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eBMI\u003c/b\u003e:body mass index; \u003cb\u003eCR\u003c/b\u003e:serum creatinine;\u003cb\u003ehs CRP\u003c/b\u003e:high-sensitivity c-reactive protein\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison across eGFR.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical Data\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eeGFR(\u0026lt;90)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;325)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eeGFR(\u0026gt;=90)\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;584)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender(n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(mean (SD)), y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.89(7.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.13(10.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139.67(18.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137.37(17.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edBP(mean (SD)), mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.01(10.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.67(10.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHight(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163.31(7.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168.36(7.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(mean (SD)), kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.56(9.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.51(11.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(mean (SD)), kg/m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.17(3.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.87(3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWaist circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.67(45.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91.11(9.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip circumference(mean (SD)), cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94.40(5.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.42(6.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 0min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.84(3.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.32(3.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eglucose 120min(mean (SD)),mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.54(4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.18(4.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1C(mean (SD)), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.90(2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.18(2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 0min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.02(1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.50(33.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC peptide 120min(mean (SD)),\u0026micro;g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.42(2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.98(66.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLp(a) (mean (SD)), mg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165.30(158.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145.15(127.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.75(6.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.37(1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.40(0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.48(1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL(mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.26(0.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.50(6.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.49(13.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.07(7.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.87(29.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.63(14.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA (mean (SD)), \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309.07(97.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e299.53(81.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mean (SD)), mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.75(6.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.37(1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehsCRP(mean (SD)),mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.42(10.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.84(7.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cb\u003esBP\u003c/b\u003e:systolic Blood pressure; \u003cb\u003edBP\u003c/b\u003e: diastolic blood pressure; \u003cb\u003eBMI\u003c/b\u003e:body mass index; \u003cb\u003eCR\u003c/b\u003e:serum creatinine;\u003cb\u003ehs CRP\u003c/b\u003e:high-sensitivity c-reactive protein\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor UACR classification (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), patients were divided into three groups: \u0026lt;2.5, 2.5\u0026ndash;30, and \u0026gt;\u0026thinsp;30 mg/mL. Comparative analysis of VD levels and other clinical parameters across these groups revealed significant variations in multiple measures. These included fasting and 2-hour postprandial blood glucose, HbA\u003csub\u003e1c\u003c/sub\u003e, blood pressure, lipid profile (TC and lipoprotein (a)), and BUN levels. Importantly, we observed an inverse relationship between ACR categories and VD levels, with mean VD concentrations decreasing as ACR increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA,P\u0026thinsp;=\u0026thinsp;0.02). Conversely, mean BUN levels showed a progressive increase with higher ACR categories. All observed differences were statistically significant.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor eGFR analysis (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), patients were stratified using a 90 mL/min/1.73 m\u0026sup2; cutoff. Significant between-group differences were observed for VD levels and other clinical parameters. Patients with eGFR \u0026lt;90 mL/min/1.73 m\u0026sup2; demonstrated significantly higher BUN(P\u0026lt;0.05) and UA(P\u0026thinsp;=\u0026thinsp;0.12)levels compared to those with higher eGFR levels. But there was no significant difference in vitamin D levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) between the two groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study included 909 patients with type 2 diabetes, stratified by their 25(OH)D levels. These groups were compared across several parameters, including BMI, blood pressure, glucose tolerance, pancreatic function, HBA\u003csub\u003e1c\u003c/sub\u003e, blood lipids, UMA, UACR, renal function, and hs-CRP levels. Significant differences were observed between the groups in age and UA(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas no significant differences were found for the other indicators. Simple linear regression analysis showed a correlation between 25(OH)D levels and patient age. Additionally, VD levels were associated with several clinical indicators, including blood UA, UMA, UCR, and UACR. Multiple linear regression analysis further revealed that VD levels were associated with age, height, weight, BMI, UA levels, and UACR. Stratification based on UACR revealed additional differences in 25(OH)D levels.\u003c/p\u003e \u003cp\u003eVD insufficiency is typically defined as levels below 30 ng/mL, while deficiency is considered below 20 ng/mL. Our study found a high prevalence of these conditions in type 2 diabetes, with 97.36% exhibiting insufficiency and 81.74% exhibiting deficiency. These findings align with international studies reporting similar high rates. A Saudi Arabian study of 1,200 patients with type 2 diabetes mellitus reported 91.3% prevalence of deficiency (serum 25(OH)D levels\u0026thinsp;\u0026lt;\u0026thinsp;20 ng/mL) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], whereas research from northern India (n\u0026thinsp;=\u0026thinsp;450) reported 94.6% insufficiency (\u0026lt;\u0026thinsp;30 ng/mL) and 76.2% deficiency (\u0026lt;\u0026thinsp;20 ng/mL) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. An Iranian study of 1,266 patients documented 81.29% deficiency prevalence (\u0026lt;\u0026thinsp;20 ng/mL) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The findings from the aforementioned studies are consistent with our results, indicating that the prevalence of VD deficiency among patients with type 2 diabetes remains high.\u003c/p\u003e \u003cp\u003eOur study further demonstrates that VD deficiency prevalence correlates significantly with established kidney disease markers (UA, CR, and UACR). This finding aligns with multiple observational studies reporting associations between serum 25(OH)D levels and diabetic complications, particularly DN [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Herrmann et al.\u0026rsquo;s cohort study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] revealed sex-specific differences in VD deficiency (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with an initial 18% higher unadjusted risk of microvascular complications (P\u0026thinsp;=\u0026thinsp;0.006) that decreased to 11\u0026ndash;14% and lost significance after adjustment for HbA\u003csub\u003e1c\u003c/sub\u003e, seasonality, or physical activity. Supporting our findings, Han et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] identified an inverse relationship between serum 25(OH)D levels and hyperuricemia in adults in the United States. Clinical evidence from RCTs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] indicates that paricalcitol, a VD receptor agonist, significantly reduces UACR in patients with type 2 diabetes mellitus, potentially through renin\u0026ndash;angiotensin system inhibition and anti-inflammatory effects.\u003c/p\u003e \u003cp\u003eThese collective findings suggest women exhibit greater susceptibility to VD deficiency, the association with metabolic markers (UA, CR, and UACR) appears particularly strong, and deficient VD levels significantly correlate with elevated CR and UACR, specifically among patients with diabetes and CKD. Pathophysiology may involve VD deficiency, which contributes to hyperuricemia via multiple pathways: inflammatory pathways [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], impaired renal excretion [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], and oxidative stress mechanisms [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDN represents a significant microvascular complication of diabetes mellitus, affecting 30\u0026ndash;40% of patients with diabetes during their lifetime. As a primary cause of ESRD [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], DN poses substantial global economic consequences. The condition typically manifests through progressive proteinuria and a declining glomerular filtration rate. Considering these clinical and economic impacts, developing strategies to prevent or delay DN progression in early disease stages is essential. Our study approach involved stratifying patients by UACR and eGFR to compare clinical indicators. The results indicate that VD status serves as an important influencing factor alongside conventional parameters like blood glucose and lipid levels. These findings suggest that early VD supplementation could potentially slow DN progression [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study has several notable strengths. First, the clinical sample size was substantial, with 909 patients with type 2 diabetes included. The sample provided adequate statistical power (\u0026gt;\u0026thinsp;80%) in this single-center retrospective study, allowing for the effective detection of associations with medium effect sizes. Second, the study addressed critical clinical questions, focusing on the relationship between VD and DN, particularly early markers of renal injury such as ACR. This focus aligns with current priorities in the prevention and management of diabetic microvascular complications. Third, the analysis incorporated multi-dimensional data. Variables including blood pressure, BMI, blood glucose, blood lipids, and HbA\u003csub\u003e1c\u003c/sub\u003e were collected, and statistical adjustment for potential confounders was performed to strengthen the validity of the observed associations between VD and nephropathy-related indicators. Finally, our study has important public health implications. VD deficiency was observed in 97% of patients with type 2 diabetes (mean level, 14 ng/ml), a rate markedly higher than that in the general population, highlighting the need for enhanced VD screening among patients with diabetes.\u003c/p\u003e \u003cp\u003eNevertheless, this study also has some limitations. First, its retrospective design introduces inherent risks of selection and recall biases. Although statistical adjustments were made for confounding factors, residual biases cannot be completely excluded. Second, the study was conducted at a single center in China, which may limit the generalizability of the findings to broader populations. Third, due to its cross-sectional nature, the study cannot establish causality; therefore, prospective cohort studies or RCTs are needed to validate these results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, this study highlights the severity of VD deficiency in patients with type 2 diabetes and its association with early kidney injury markers, offering valuable insights for clinical screening and future mechanistic investigations. Nevertheless, the observational design poses constraints, underscoring the need for further validation through longitudinal and interventional studies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e25(OH)D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003e25-hydroxyvitamin D\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eACR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eAlbumin-to-creatinine ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eBUN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eBlood urea nitrogen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eC-reactive protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eCKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eChronic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eDKD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eDiabetic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eESRD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eEnd-stage renal disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eHbA\u003csub\u003e1c\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eGlycated hemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eHDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eHigh-density lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eLDL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eLow-density lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eOGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eOral glucose tolerance test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eRCTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eRandomized controlled trials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eSCr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eSerum creatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eTC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eTotal cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eTriglycerides\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eSerum uric acid\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUACR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eUrinary albumin-to-creatinine ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eUrinary microalbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eUCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 455px;\"\u003e\n \u003cp\u003eUrinary creatinine\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and approved by The Medical Ethics Committee of the Fourth People\u0026rsquo;s Hospital of Shenyang (Approval No. 2021(11)-01). Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants (or their legal guardians) provided written informed consent for the publication of anonymized data obtained in this study. Identifying details (e.g., names, hospital IDs, dates of birth) have been removed to protect participant privacy. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDe-identified participant data are available upon reasonable request to the corresponding author.\u0026nbsp;\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\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they received financial support for the research, authorship, and publication of this article. This study was supported by the Scientific and Technical Program of Shenyang (grant number 22-321-33-61) and. Noncommunicable Chronic Diseases-National Science and Technology Major Project (grant number: 2023ZD0508100).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors met the ICMJE criteria for authorship and approved the final version of the manuscript. Individual contributions are as follows.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNL: Funding acquisition, Conceptualization, Methodology, Formal Analysis, Writing of the Original Draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJX: Data curation, Investigation, Validation, and Writing of the original draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eJS: Methodology, Software, Writing, review and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSY, FL, and FL: Writing, review, and editing. JK: Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the team of investigators, research partners, and operational staff involved in this study. We also extend gratitude to Editage (editage.com/frontiers) for their linguistic assistance during the preparation of this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGiustina, A. et al. Consensus Statement on Vitamin D Status Assessment and Supplementation: Whys, Whens, and Hows. \u003cem\u003eEndocr. 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Nephrol.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (12), 1977\u0026ndash;1986. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1681/ASN.2012040383\u003c/span\u003e\u003cspan address=\"10.1681/ASN.2012040383\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetic nephropathy, New therapeutic targets, Type 2 diabetes, Vitamin D","lastPublishedDoi":"10.21203/rs.3.rs-6879564/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6879564/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGiven the unclear role of vitamin D (VD) deficiency in early kidney injury, this study aimed to investigate the association between VD status and diabetic nephropathy (DN) in patients with type 2 diabetes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study included 909 patients with type 2 diabetes mellitus who received treatment at the Department of Endocrinology and Metabolism of the Fourth People\u0026rsquo;s Hospital of Shenyang between July and December 2022. Participants were grouped according to serum 25-hydroxyvitamin D [25(OH)D] levels: \u0026lt;10, 10\u0026ndash;20, 20\u0026ndash;30, and \u0026ge;\u0026thinsp;30 ng/mL. Clinical data, including blood pressure, body mass index, waist circumference, fasting blood glucose, lipid profiles, glycated hemoglobin (HbA\u003csub\u003e1c\u003c/sub\u003e), C-reactive protein, and urinary albumin-to-creatinine ratio (UACR), were collected. DN was defined based on UACR levels and estimated glomerular filtration rate (eGFR) after excluding other causes of kidney disease. Associations between VD levels and clinical parameters were assessed using linear and logistic regression analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of VD deficiency (\u0026lt;\u0026thinsp;20 ng/mL) among patients with type 2 diabetes was 81.7%, with 97% exhibiting insufficiency (\u0026lt;\u0026thinsp;30 ng/mL) and a mean VD level of 14\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9 ng/mL. Simple linear regression analysis revealed a correlation of VD levels with age, uric acid, and urinary albumin-to-creatinine ratio (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Furthermore, patient stratification by VD levels revealed significant differences in age and uric acid levels among the groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Additionally, grouping based on albumin-to-creatinine ratio exhibited significant differences in VD levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe prevalence of VD deficiency is extremely high among patients with type 2 diabetes and serves as an early indicator of kidney disease, highlighting the need for early screening and potential intervention.\u003c/p\u003e","manuscriptTitle":"High Prevalence of Vitamin D Deficiency and Its Association with Early Markers of Kidney Injury in Type 2 Diabetes:A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-25 09:41:52","doi":"10.21203/rs.3.rs-6879564/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"db209ca6-9a1b-4d3d-92b5-02d40468490f","owner":[],"postedDate":"June 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50307867,"name":"Health sciences/Endocrinology/Endocrine system and metabolic diseases"},{"id":50307868,"name":"Health sciences/Nephrology/Kidney diseases/Chronic kidney disease"}],"tags":[],"updatedAt":"2025-07-02T09:53:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-25 09:41:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6879564","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6879564","identity":"rs-6879564","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}