Association of vitamin D levels with bone density in patients with osteoporosis

Association of vitamin D levels with bone density in patients with osteoporosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of vitamin D levels with bone density in patients with osteoporosis Mitra Abbasifard, Kosar Jafarizadeh, Mobina Taghipoor, Zahra Bagheri-Hosseinabadi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4930139/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 Osteoporosis is a prevalent skeletal disorder characterized by reduced bone mass and deterioration of bone microarchitecture, leading to an increased risk of fractures. Given the growing recognition of the association between vitamin D (VitD) and bone health, there is a pressing need to conduct studies focusing on the level of VitD and its correlation with bone mineral density (BMD) in osteoporosis patients. This study aims to address this critical knowledge gap by exploring the association between VitD levels and bone mineral density in osteoporosis patients from an Iranian population. Methods We recruited 500 subjects with osteoporosis and 500 non-osteoporosis cases. The BMD of the cases was measured in the hip, femur neck, and L1-L4 spine using the Stratos device via DXA method. VitD level was measured in the serum of study participants using ELISA. Results VitD level was significantly lower in the osteoporosis cases (31.15 ± 9.44 nmol/L) compared to the non-osteoporosis subjects (41.65 ± 10.25 nmol/L). It was significantly higher in the male subjects compared to female patients in the osteoporosis group ( P = 0.048). In both osteoporosis ( P = 0.008) and non-osteoporosis ( P = 0.001) subjects, the level of VitD was significantly lower in the subjects with a history of bone fracture compared to those without a history of bone fracture. The VitD level had significantly positive correlation with the BMD of hip ( r = 0.44, P = 0.001), spine, and femur. Conclusions VitD deficiency in the osteoporosis patients is associated with BMD and bone fractures. Vitamin D Osteoporosis Bone mineral density Bone fracture Introduction Osteoporosis, also known as "brittle bone disease" or "porous bone," is a skeletal disorder characterized by the deterioration of bone tissue and loss of bone mass. It commonly occurs in old age and is considered the primary cause of bone fractures worldwide [ 1 ]. The World Health Organization (WHO) defines osteoporosis as a reduction in bone density of 2.5 standard deviations or more below the average peak bone density in young, healthy individuals [ 2 ]. Unlike many chronic diseases that manifest various symptoms, osteoporosis often remains asymptomatic until a bone fracture occurs. It can lead to fractures in different areas of the body, such as the spine, hips, and wrists [ 3 ]. Hip fractures are particularly severe and associated with high mortality rates [ 4 ]. Additionally, osteoporosis-related fractures tend to occur in areas that are uncommon in healthy individuals [ 4 ]. Osteoporosis affects both genders, but its prevalence is much higher in women than in men [ 5 ]. The prevalence of the disease varies across different regions, with approximately 200 million people worldwide estimated to be affected. In the United States, about 10 million individuals have been diagnosed with osteoporosis, and an additional 34 million have low bone mass, putting them at risk of developing osteoporosis [ 6 ]. Diagnosis of osteoporosis is based on clinical history, clinical signs, and bone mass estimation tests [ 7 ]. Radiological evidence can also aid in diagnosis [ 8 ]. Dual-energy x-ray absorptiometry (DXA) is considered the gold standard for bone mass estimation due to its repeatability, non-invasiveness, short examination time, and minimal radiation exposure. The results are reported as T-scores, with T-score − 1 or higher indicating normal bone density, T-score between − 1 and − 2.5 indicating low bone density (osteopenia), and T-score − 2.5 or lower indicating osteoporosis [ 9 , 10 ]. Osteoporosis is influenced by various factors. With advancing age, bone tissue breakdown exceeds its formation, leading to an increased risk of osteoporosis in older individuals [ 11 ]. Alcohol consumption, smoking, and certain medications, especially glucocorticoids, can also contribute to osteoporosis [ 12 , 13 ]. Other factors such as physical inactivity, weight loss of more than 10% of body weight compared to young adulthood, or a body mass index (BMI) below 19 are associated with an increased risk of osteoporosis [ 14 , 15 ]. Additionally, several genetic variations and single nucleotide polymorphisms (SNPs) have been associated with osteoporosis risk. Specific genes involved in bone formation, remodeling, and mineralization have been identified, and certain variations in these genes can influence bone health and increase susceptibility to osteoporosis [ 16 ]. Vitamin D (VitD) deficiency is another significant factor associated with osteoporosis [ 17 ]. VitD deficiency is a common nutritional deficiency worldwide, with over 40% of adults over the age of 50 estimated to be deficient [ 18 ]. Deficiency in VitD may impress osteoporosis proneness via impaired calcium absorption, altered bone remodeling, reduced bone mineralization, and reduced bone density [ 19 ]. VitD, a steroid hormone, plays a crucial role in bone mineralization and other metabolic processes, including skeletal growth [ 20 ]. Its main role in bone metabolism is to increase plasma calcium and phosphate levels, which are essential for mineralization. It also promotes proper nerve transmission, neuromuscular junctions, and the secretion of hormones, especially parathyroid hormone (PTH). These mechanisms increase bone mineral density, reducing the risk of osteoporosis and its consequences [ 21 ]. While a concentration between 50 nmol/L to 125 nmol/L is usually considered as the normal levels of VitD, VitD insufficiency is often defined as having levels between 30 nmol/L and 50 nmol/L, and VitD deficiency is typically defined as having levels below 30 nmol/L [ 18 ]. The status of VitD can vary among individuals in different countries and even within regions of the same country due to physical differences, human race, and environmental factors. Factors such as impaired absorption, limited sunlight exposure, and increased demand for rapid growth can contribute to VitD deficiency. A deficiency in VitD negatively affects calcium metabolism, osteoblastic activity, bone matrix synthesis, bone remodeling, and bone density [ 22 ]. In adults, low VitD levels are associated with osteomalacia, osteopenia, osteoporosis, and related fractures [ 23 ]. Furthermore, observational studies have shown that low 25-hydroxy VitD levels are associated with an increased risk of various non-skeletal diseases, including cancer, infections, autoimmune diseases, and cardiovascular disease (CVD) [ 24 – 26 ]. Given the information provided, we sought to determine the serum VitD levels in patients with osteoporosis who visited the Densitometry Center in Rafsanjan city during the first six months of 2022. VitD level assessment plays an important role in diagnosing and managing osteoporosis. We hope that conducting this study will contribute effectively to the prevention of osteoporosis and related complications such as fractures. Methods Study subjects This research was carried out on individuals who were referred to the Densitometry Center of Rafsanjan city, Iran, during the initial half of 2022. A total of 500 patients with osteoporosis and 500 individuals without osteoporosis were selected as the control group. The BMD of the participants was measured at the hip, femur neck, and L1-L4 spine while lying on their back using the Stratos device (DMS IMAGING, France) and the DXA method. Based on the WHO's recommended criteria, subjects with a T score less than − 2.5 were classified as having osteoporosis, and subjects with a T score greater than − 1 were considered part of the control group [ 27 ]. The inclusion criteria for the study were as follows: not having conditions, such as liver and kidney failure, thyroid and parathyroid disorders, hematological diseases (such as anemia, thrombocytopenia, leukopenia), malignancies, autoimmune diseases (such as ankylosing spondylitis, rheumatoid arthritis, lupus, etc.), not being pregnant, having no active infections, or blood transfusion in the last year, and not taking medications like bisphosphonates, selective estrogen receptor modulators, denosumab, steroids, and VitD metabolism affecting medications like phenytoin. Finally, a 5 ml sample of whole blood was collected to assess the serum VitD levels. Table 1 presents the baseline data and biochemical indexes of the participants in the study. The research received approval from the ethics committee of Rafsanjan University of Medical Sciences (IR.RUMS.REC.1401.080), and written informed consent was obtained from all the participants involved in the study. Table 1 Baseline data, demographics, clinical, and laboratory measurements of the study participants. Variable Osteoporosis (n = 500) Non-osteoporosis (n = 500) P value Age (Year); Mean ± SD 69.5 ± 18.3 67.7 ± 20.4 > 0.05 Sex (male/Female); n (%) 44 (8.8%)/ 456 (91.2%) 49 (9.8%)/ 451 (90.2%) > 0.05 Career status (working/ household); n (%) 388 (77.6%)/ 112 (22.4%) 394 (78.8%)/ 106 (21.2%) > 0.05 Marital status (married/ single); n (%) 481 (96.2%)/ 19 (3.8%) 477 (95.4%)/ 23 (4.6%) > 0.05 Education (illiterate/ educated); n (%) 89 (17.8%)/ 411 (82.2%) 74 (14.8%)/ 426 (85.2%) > 0.05 Living area (urbane/ rural); n (%) 411 (82.2%)/ 89 (17.8) 429 (85.5%)/ 71 (14.5%) > 0.05 Smoking (yes/ no); n (%) 41 (8.2%)/ 459 (91.8%) 58 (11.6%)/ 442 (88.4%) > 0.05 BMI (kg/m 2 ); Mean ± SD 29.11 ± 5.69 28.13 ± 4.88 > 0.05 Menarche age in females (Year); Mean ± SD 13.10 ± 1.88 12.4 ± 1.25 > 0.05 Menopause duration in females (Year); Mean ± SD 10.5 ± 1.70 9.85 ± 1.50 > 0.05 WBC (cells/mm 3 ); Mean ± SD 7439 ± 1159 6388 ± 1258 > 0.05 Platelet count (cells/mm 3 ); Mean ± SD 234000 ± 23000 245000 ± 16000 > 0.05 Hemoglobin (g/dl); Mean ± SD 11.69 ± 2.14 14.10 ± 3.88 0.05 ALP (IU/L); Mean ± SD 135.56 ± 38.36 129.50 ± 34.25 > 0.05 AST (IU/L); Mean ± SD 23.47 ± 9.20 21.22 ± 10.11 > 0.05 ALT (IU/L); Mean ± SD 29.14 ± 8.30 30.14 ± 8.25 > 0.05 CRP (mg/L); Mean ± SD 4.25 ± 1.65 1.48 ± 0.55 < 0.05 ESR (mm/h); Mean ± SD 19.20 ± 5.26 7.14 ± 1.61 < 0.05 FBS (mg/dl); Mean ± SD 114.6 ± 41.25 101.14 ± 24.13 0.05 TG (mg/dl); Mean ± SD 114.30 ± 31.84 105.14 ± 28.51 > 0.05 LDL (mg/dl); Mean ± SD 117.40 ± 28.44 105.32 ± 27.44 > 0.05 HDL (mg/dl); Mean ± SD 47.20 ± 7.89 48.25 ± 6.33 > 0.05 Creatinine (mg/dl); Mean ± SD 1.11 ± 0.23 1.02 ± 0.64 > 0.05 BUN (mg/dl); Mean ± SD 16.34 ± 7.41 15.65 ± 7.25 > 0.05 Vitamin D level (nmol/L); Mean ± SD 31.15 ± 9.44 41.65 ± 10.25 < 0.05 Bone fracture history (yes/ no); n (%) 91 (18.2%)/ 409 (81.8%) 21 (4.2%)/ 479 (95.8%) 0.05 Vitamin D supplement use (yes/ no); n (%) 392 (78.4%)/ 108 (21.6%) 211 (42.2%)/ 289 (57.8%) 0.05 Co-morbidity (diabetes, hypertension) (yes/ no); n (%) 81 (16.2%)/ 419 (83.8%) 48 (96%)/ 452 (4%) < 0.05 Drug (anti-hypertension, diabetes) use (yes/ no); n (%) 81 (16.2%)/ 419 (83.8%) 48 (96%)/ 452 (4%) < 0.05 BMI; Body-mass index, WBC; White blood cell, RBC; Red blood cell, ALP; Alkaline phosphatase, AST; Aspartate aminotransferase, ALT; Alanine aminotransferase, CRP; C-reactive protein, ESR; Erythrocyte sedimentation rate, FBS; Fasting blood sugar, TC; Total cholesterol, TG; Triglyceride, LDL; Low-density lipoprotein, HDL; High-density lipoprotein, BUN; Blood urea nitrogen, SD; Standard deviation Laboratory measurements The levels of various substances in the blood were assessed through enzymatic colorimetric methods after an overnight fasting. Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Fasting blood sugar (FBS), Triglyceride (TG), Low density lipoprotein (LDL), High density lipoprotein (HDL), Creatinine, and Blood urea nitrogen (BUN) concentrations were determined using these methods. Erythrocyte sedimentation rate (ESR) was measured through the automated kinetic photometric method. Additionally, the level of C-reactive protein (CRP) was measured using the nephelometric method. The count of blood cells and hematologic indices was determined using the complete blood count (CBC) test performed with the Sysmex KX-21N Hematology Analyzer (Sysmex, Japan). Determination of serum VitD levels The level of VitD in serum samples of study subjects was measured using Enzyme linked immunosorbent assay (ELISA) by a commercial kit (R&D system, USA) based on manufacturer’s protocols. Statistical analysis GraphPad Prism v.9.00 for Windows (La Jolla, CA, USA) was utilized for graph design and statistical comparisons. The normality of quantitative data was assessed using the Shapiro-Wilk test. Group comparisons of non-parametric variables were conducted using the Mann–Whitney U test. To examine potential correlations between scale variables, the Spearman's correlation test was employed. The study results were presented as mean ± Standard deviation (SD), and P values < 0.05 were considered statistically significant. Result Subjects’ characteristics Table 1 demonstrates the baseline data, demographics and laboratory data of the study groups. The study participants composed of 44 (8.8%) males and 456 (91.2%) females in the osteoporosis group and 49 (9.8%) males and 451 (90.2%) females in the non-osteoporosis group. The mean age of the osteoporosis and non-osteoporosis groups was 69.5 ± 18.3 and 67.7 ± 20.4 years, respectively. There were no statistically significant differences in both the gender distribution and age between the study groups and therefore, the study subjects were matched for age and gender. The hemoglobin concentration was significantly lower in the osteoporosis group in comparison to the non-osteoporosis group. The levels of CRP, ESR, and FBS were significantly higher in the osteoporosis group in comparison to the non-osteoporosis subjects. History of bone fracture was significantly higher in the osteoporosis group [91 (18.2%)] compared to the non-osteoporosis subjects [21 (4.2%)]. Furthermore, the number of cases using VitD supplement was significantly higher in the osteoporosis subjects [392 (78.4%)] in comparison to the non-osteoporosis individuals [211 (42.2%)]. However, sunscreen use and sun exposure were not significantly different between the study groups (Table 1 ). Z-score, T-score, and BMD Z-score and T-score of Hip, Z-score and T-score of spine, and Z-score and T-score of femur were all significantly lower in the osteoporosis patients compared to non-osteoporosis subjects. In addition, BMD of hip, spine, and femur was significantly lower in the osteoporosis group in comparison to the non-osteoporosis group (Table 2 ). Table 2 Z-score, T-score, and BMD of hip, spine, and femur in the study groups. Scoring Osteoporosis Non-osteoporosis P Value Z-score Hip; Mean ± SD -2.2 ± 0.3 -0.1 ± 0.3 0.0001 T-score Hip; Mean ± SD -2.1 ± 0.4 -0.2 ± 0.1 0.0001 Z-score Spine; Mean ± SD -3.3 ± 0.7 -0.1 ± 0.2 0.0001 T-score Spine; Mean ± SD -3.5 ± 0.8 -0.6 ± 0.1 0.0001 Z-score Femur; Mean ± SD -2.8 ± 0.8 -0.1 ± 0.4 0.0001 T-score Femur; Mean ± SD -2.9 ± 0.7 -0.2 ± 0.3 0.0001 Spine BMD (g/cm 2 ); Mean ± SD 0.842 ± 0.142 1.342 ± 0.234 0.0001 Hip BMD (g/cm 2 ); Mean ± SD 0.471 ± 0.082 1.281 ± 0.350 0.0001 Femur BMD (g/cm 2 ); Mean ± SD 0.944 ± 0.111 1.482 ± 0.171 0.0001 SD; Standard deviation, BMD; Bone mineral density VitD levels It was detected that VitD level was significantly lower in the osteoporosis cases (31.15 ± 9.44 nmol/L) compared to the non-osteoporosis subjects (41.65 ± 10.25 nmol/L) (Table 1 ). VitD level was significantly higher in the male subjects compared to female patients in the osteoporosis group ( P = 0.048), while it was not significantly different between the male and female subjects of the non-osteoporosis subjects ( P = 0.128). In both osteoporosis ( P = 0.008) and non-osteoporosis ( P = 0.001) subjects, the level of VitD was significantly lower in the subjects with a history of bone fracture compared to those without a history of bone fracture. Furthermore, in both osteoporosis ( P = 0.004) and non-osteoporosis ( P = 0.001) groups, the level of VitD was significantly lower in the cases using sunscreen compared to those not using sunscreen. In cases using VitD supplement, the level of VitD was significantly higher in both the osteoporosis ( P = 0.001) and non-osteoporosis ( P = 0.001) subjects (Table 3 ). Table 3 Vitamin D level in the study groups based on the specifications of the subjects. Variable Vitamin D level (nmol/L); Mean ± SD Osteoporosis P value Non-osteoporosis P value Sex (male/ female) 34.05 ± 9.93/ 28.25 ± 8.95 0.048 42.16 ± 10.8/ 41.14 ± 9.7 0.128 Smoking (smoker/ non-smoker) 30.14 ± 9.19/ 32.16 ± 9.69 0.255 40.32 ± 10.26/ 42.98 ± 10.24 0.321 Career status (working/ household) 31.1 ± 9.4/ 31.2 ± 9.48 0.321 41.36 ± 10.3/ 41.94 ± 10.2 0.321 Marital status (married/ single) 31.26 ± 9.58/ 31.04 ± 9.3 0.214 40.66 ± 10.11/ 42.64 ± 10.39 0.655 Education (illiterate/ educated) 31.05 ± 9/ 31.25 ± 9.88 0.388 41.22 ± 10.29/ 42.08 ± 10.21 0.236 Living area (urbane/ rural) 30.1 ± 8.89/ 32.2 ± 9.99 0.097 39.8 ± 10.09/ 43.5 ± 10.41 0.068 Bone fracture history (yes/ no) 27.85 ± 8.14/ 34.45 ± 10.17 0.008 39.5 ± 9.95/ 43.8 ± 10.55 0.001 Sunscreen use (yes/ no) 25.11 ± 7.29/ 37.19 ± 11.59 0.004 37.56 ± 8.85/ 45.74 ± 11.65 0.001 Vitamin D supplement use (yes/ no) 32.76 ± 10.11/ 29.54 ± 8.77 0.001 59.24 ± 12.81/ 24.06 ± 7.69 0.001 Co-morbidity (yes/ no) 29.4 ± 8.85/ 32.9 ± 10.03 0.077 38.98 ± 9.77/ 44.32 ± 10.73 0.121 Drug use (yes/ no) 29.59 ± 9.11/ 32.71 ± 9.78 0.084 38.54 ± 9.8/ 44.76 ± 10.7 0.168 Correlation analysis The correlation analysis was performed between the VitD levels and patients’ data in the osteoporosis group (Table 4 ). It was seen that the VitD level had significantly positive correlation with the sun exposure duration ( r = 0.29, P = 0.039). Analysis revealed that VitD level had negative significant correlation with Z-score Hip ( r = -0.41, P = 0.001), T-score Hip ( r = -0.55, P = 0.001), Z-score Spine ( r = -0.49, P = 0.001), T-score Spine ( r = -0.48, P = 0.001), Z-score femur ( r = -0.58, P = 0.001), and T-score femur ( r = -0.59, P = 0.001) in the osteoporosis patients. The VitD level had significantly positive correlation with the BMD of hip ( r = 0.44, P = 0.001), spine ( r = 0.56, P = 0.001), and femur ( r = 0.60, P = 0.001) (Table 4 ). Table 4 Analysis of correlation between the Vitamin D level and data of cases with osteoporosis. Variable VitD level Variable VitD level r P r P Age 0.11 0.172 TG 0.09 0.212 BMI 0.10 0.220 LDL 0.10 0.142 Menarche age 0.07 0.254 HDL 0.07 0.354 Menopause duration 0.04 0.958 Creatinine 0.13 0.334 WBC count 0.12 0.141 BUN 0.10 0.376 Platelet count 0.05 0.740 Sun exposure duration 0.29 0.039 Hemoglobin 0.12 0.326 Z-score Hip; Mean ± SD -0.41 0.001 RBC count 0.14 0.214 T-score Hip; Mean ± SD -0.55 0.001 ALP 0.07 0.419 Z-score Spine; Mean ± SD -0.49 0.001 AST 0.09 0.138 T-score Spine; Mean ± SD -0.48 0.001 ALT 0.11 0.192 Z-score Femur; Mean ± SD -0.58 0.001 CRP 0.09 0.291 T-score Femur; Mean ± SD -0.59 0.001 ESR 0.07 0.359 Spine BMD; Mean ± SD -0.54 0.001 FBS 0.14 0.646 Hip BMD 0.44 0.001 TC 0.10 0.484 Spine BMD 0.56 0.001 Femur BMD 0.60 0.001 BMI; Body-mass index, WBC; White blood cell, RBC; Red blood cell, ALP; Alkaline phosphatase, AST; Aspartate aminotransferase, ALT; Alanine aminotransferase, CRP; C-reactive protein, ESR; Erythrocyte sedimentation rate, FBS; Fasting blood sugar, TC; Total cholesterol, TG; Triglyceride, LDL; Low-density lipoprotein, HDL; High-density lipoprotein, BUN; Blood urea nitrogen, BMD; Bone mineral density Discussion While there is existing research on the relationship between VitD and bone health, there are gaps and inconclusive observations in the evidence specific to osteoporosis patients in Iranian population. In addition, Osteoporosis prevalence and risk factors can vary across different populations. By focusing on a specific population, we intended to address the relevance of VitD levels to bone health in the context of local genetics, lifestyle, and environmental factors. Hence, we performed this study to determine the serum VitD levels in patients with osteoporosis who visited the Densitometry Center in Rafsanjan city during the first six months of 2022. VitD level assessment plays an important role in diagnosing and managing osteoporosis. Understanding the association between VitD levels and BMD in osteoporosis patients can have significant clinical implications. It may help healthcare professionals develop targeted treatment strategies, such as personalized VitD supplementation, to improve bone health outcomes and prevent further bone loss. A recent systematic review and meta-analysis research indicated that a combination of VitD and calcium could be able to significantly diminish the risk of fractures in the osteoporotic patients [ 28 ]. Additionally, results of this study emphasized that the positive impact of combination of VitD and calcium supplementation on bone formation remained consistent over a period of three years, providing further evidence of its beneficial effect on bone structure [ 29 ]. In consistent with these observations, our study indicated that level of VitD was lower in the osteoporosis patients. Furthermore, VitD levels had statistically significant correlation with BMD in the hip, spine, and femur. Javadi et al . conducted a study in 2003 to evaluate the relationship between calcium and VitD intake, serum calcium and VitD levels, BMD, and osteoporosis in individuals living in Tehran, Iran. Blood sampling was performed in the winter at the participants' residences. The study included 830 participants aged 20 to 76 years, with 39.2% being males and 60.8% females. The study revealed that VitD levels were lower in men compared to women, and serum calcium levels were higher in men. Calcium and VitD intake were higher in men compared to women. The total calcium intake, along with VitD intake, was found to predict serum calcium levels. The study indicated that the dietary intake of calcium in the studied population only covered 50–60% of the daily requirement, while VitD intake covered approximately 15% [ 30 ]. Pourhashem et al . conducted a study in 2012 to evaluate the prevalence of osteoporosis and its association with serum VitD levels in elderly residents of northern Iran. The study found that the overall prevalence of osteoporosis in at least one site was 32% (28.5% in the lumbar spine and 14.5% in the femoral neck). The prevalence of osteoporosis was 7.55% in women and 4.12% in elderly men. The BMD in the femoral neck showed a negative correlation with age but did not show any significant association with serum VitD levels in the study [ 31 ]. Rahmati et al . conducted a study in 2016 to assess the prevalence of VitD deficiency among individuals referred to laboratories in the city of Ilam (north of Iran). The study included 2919 participants, of which 70.3% were women. The overall prevalence of VitD deficiency in individuals was estimated to be approximately 62%. Severe and moderate VitD deficiencies were found in 10.4% and 51.5% of the participants, respectively. The prevalence of VitD deficiency in the age groups 1–6, 7–18, 19–60, and above 60 years was 45%, 59%, 64%, and 58%, respectively. The mean serum level of VitD was 36.25 ± 18.79 ng/mL. The study also showed a statistically significant association between VitD deficiency and age and gender. The group concluded that the high prevalence of VitD deficiency calls for intervention measures to prevent its consequences, such as pharmaceutical treatment and food enrichment programs to increase VitD intake [ 32 ]. Our research also revealed that VitD levels is lower in the patients with osteoporosis compared to non-osteoporosis subjects. In addition, its level was lower in the female subjects compared to male patients. In a study conducted by Papadakis et al . in 2015 to investigate seasonal changes in serum VitD levels in osteoporosis patients, the serum VitD level was examined in 596 patients (mean age of 65.3 years) at different time intervals over a period of 2.5 years. The findings indicated that the minimum serum level was observed in March, while the maximum levels were recorded in August, September, and October. The prevalence of VitD deficiency and insufficiency in March was 76.5% and 7.8%, respectively. In contrast, the highest prevalence of VitD sufficiency was observed in August, September, and October (38.1%, 45.3%, and 46.5%, respectively), indicating that seasonal variations significantly affect the VitD levels in these patients [ 33 ]. Our research, on the other hand, focused on determining the overall VitD levels in a population of osteoporosis patients and provided an essential baseline understanding of VitD status in this group. While we did not delve into the seasonal variations, it serves as a comprehensive snapshot of the VitD status at a specific point in time, offering valuable data on the general prevalence of VitD deficiency or sufficiency in the population. However, by exploring the relationship between VitD and BMD as well as T-score and Z-score of hip, spine, and femur, our study provides insights into the potential impact of VitD status on bone health in this specific patient group. Understanding this association is vital as VitD plays a key role in calcium absorption and bone metabolism, which directly influences bone density and strength. In conclusion, our study findings have demonstrated a significant association between lower VitD levels and reduced BMD in osteoporosis subjects within the Iranian population. Moreover, we observed a higher incidence of bone fractures among individuals with lower VitD levels. The implications of these results in clinical practice are substantial. Healthcare professionals, especially those dealing with osteoporosis patients, should consider VitD assessment as an essential component of their evaluation. Identifying individuals with VitD deficiency or insufficiency can help in early detection and prompt intervention to optimize VitD levels and potentially improve bone health outcomes. As a limitation of this study, we did not include patients with osteopenia, that could have been yielding further insights in the VitD deficiency and BMD and bone fracture. As for further studies, several areas could benefit from additional research. Firstly, longitudinal studies can be conducted to investigate the long-term effects of VitD supplementation on BMD and fracture risk reduction in osteoporosis patients. Such studies can provide more comprehensive data on the sustained impact of VitD interventions over an extended period. Secondly, clinical trials that evaluate the specific dosage and duration of VitD supplementation in osteoporosis patients can help establish evidence-based guidelines for its use. These trials may compare different VitD dosages and examine their effects on BMD, fracture incidence, and overall bone health. Additionally, it would be valuable to investigate the potential interactions between VitD and other factors that influence bone health, such as calcium intake, physical activity, and genetic factors. Understanding these interactions can lead to a more comprehensive approach to osteoporosis management, targeting multiple aspects that contribute to bone health. Furthermore, research focusing on diverse populations and various geographic regions can provide insights into potential variations in VitD status and its association with osteoporosis risk across different demographics and environments. Declarations Ethics approval and consent to participate The study protocol was approved from the local Human Research Ethics Committee located in Rafsanjan University of Medical Sciences (IR.RUMS.REC.1401.080) and written informed consent form was taken by all subjects. All methods were carried out in accordance with relevant guidelines and regulations provided by Rafsanjan University of Medical Sciences. Research carried out here were in compliance with the Helsinki Declaration. Consent for publication Not applicable. Availability of data and materials The datasets analyzed and generated during the study are available from the corresponding author on reasonable request. Competing interests Mitra Abbasifard, Kosar Jafarizadeh, Mobina Taghipoor, and Zahra Bagheri-Hosseinabadi declare that they have no conflict of interest. Funding This study was financially supported by a grant from the Rafsanjan University of Medical Sciences, Rafsanjan, Iran. Authors' Contributions MA ; examined the patients, participated in manuscript preparation, and read the manuscript critically. KJ ; Contributed in performing the experiments, participated in manuscript preparation and read the manuscript critically. MT ; Performed the statistical analysis, participated in manuscript preparation, and read the manuscript critically. ZBH ; Developed the main idea, Performed the experiments, take the financial support, participated in manuscript preparation and read the manuscript critically. Acknowledgements The authors are grateful of the patients and the healthy individuals for their participation in the study. References Rachner TD, Khosla S, Hofbauer LC. Osteoporosis: now and the future. Lancet. 2011;377(9773):1276–87. Czerwiński E, Badurski JE, Marcinowska-Suchowierska E, Osieleniec J. Current understanding of osteoporosis according to the position of the World Health Organization (WHO) and International Osteoporosis Foundation. Ortop Traumatol Rehabil. 2007;9(4):337–56. Sözen T, Özışık L, Başaran NÇ. An overview and management of osteoporosis. Eur J Rheumatol. 2017;4(1):46. Lin JT, Lane JM. Osteoporosis: a review. Clinical Orthopaedics and Related Research (1976–2007). 2004;425:126 – 34. 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A comprehensive overview on osteoporosis and its risk factors. Therapeutics and clinical risk management. 2018:2029–49. Geusens PP, van den Bergh JP. Osteoporosis and osteoarthritis: shared mechanisms and epidemiology. Curr Opin Rheumatol. 2016;28(2):97–103. Buckley L, Humphrey MB. Glucocorticoid-induced osteoporosis. N Engl J Med. 2018;379(26):2547–56. Mazocco L, Chagas P. Association between body mass index and osteoporosis in women from northwestern Rio Grande do Sul☆. Revista brasileira de reumatologia. 2017;57:299–305. Castrogiovanni P, Trovato FM, Szychlinska MA, Nsir H, Imbesi R, Musumeci G. The importance of physical activity in osteoporosis. From the molecular pathways to the clinical evidence. 2016. Hosoi T. Genetic aspects of osteoporosis. J Bone Miner Metab. 2010;28:601–7. Lips P, Van Schoor NM. The effect of vitamin D on bone and osteoporosis. Best Pract Res Clin Endocrinol Metab. 2011;25(4):585–91. Amrein K, Scherkl M, Hoffmann M, Neuwersch-Sommeregger S, Köstenberger M, Tmava Berisha A, et al. Vitamin D deficiency 2.0: an update on the current status worldwide. Eur J Clin Nutr. 2020;74(11):1498–513. Brincat M, Gambin J, Brincat M, Calleja-Agius J. The role of vitamin D in osteoporosis. Maturitas. 2015;80(3):329–32. Jenkinson C. The vitamin D metabolome: An update on analysis and function. Cell Biochem Funct. 2019;37(6):408–23. Bikle DD, Vitamin D. Newer concepts of its metabolism and function at the basic and clinical level. J Endocr Soc. 2020;4(2):bvz038. Voulgaridou G, Papadopoulou SK, Detopoulou P, Tsoumana D, Giaginis C, Kondyli FS, et al. Vitamin D and calcium in osteoporosis, and the role of bone turnover markers: A narrative review of recent data from RCTs. Diseases. 2023;11(1):29. Prentice A, Vitamin. D deficiency: a global perspective. Nutr Rev. 2008;66(suppl2):S153–64. Lakkireddy M, vardhan Mudavath S, Karra ML, Arora AJ. Hypovitaminosis D in patients with osteoporotic hip fractures. J Clin Orthop trauma. 2019;10(4):768–73. Matyjaszek-Matuszek B, Lenart-Lipińska M, Woźniakowska E. Clinical implications of vitamin D deficiency. Menopause Review/Przegląd Menopauzalny. 2015;14(2):75–81. Bouillon R, Eelen G, Verlinden L, Mathieu C, Carmeliet G, Verstuyf A. Vitamin D and cancer. J Steroid Biochem Mol Biol. 2006;102(1–5):156–62. Kanis JA. Diagnosis of osteoporosis and assessment of fracture risk. Lancet. 2002;359(9321):1929–36. Eleni A, Panagiotis P. A systematic review and meta-analysis of vitamin D and calcium in preventing osteoporotic fractures. Clin Rheumatol. 2020;39(12):3571–9. 10.1007/s10067-020-05122-3 . Porthouse J, Cockayne S, King C, Saxon L, Steele E, Aspray T, et al. Randomised controlled trial of calcium and supplementation with cholecalciferol (vitamin D3) for prevention of fractures in primary care. BMJ. 2005;330(7498):1003. Hossein-nezhad A, Khalili-Fard A, Maghbooli J. Correlation between bone mineral density and osteoporosis With Ca and vitamin D intake. Zahedan J Res Med Sci. 2003;5(1). Pourhashem Z, Bayani M, Noreddini H, Bijani A, Hosseini SR. Prevalence of osteoporosis and its association with serum vitamin D level in older people in Amirkola, North of Iran. Caspian J Intern Med. 2012;3(1):347. Rahmati S, Yadegarazadi A, Shamloo B, Rabiei Fakhr F, Azami M, Borji M, et al. The frequency of vitamin d deficiency among referred to clinical laboratories in Eyvan city during 2015 and 2016-Ilam province. Iran SSU_Journals. 2016;24(3):261–8. Papadakis G, Keramidas I, Kakava K, Pappa T, Villiotou V, Triantafillou E, et al. Seasonal variation of serum vitamin D among Greek female patients with osteoporosis. vivo. 2015;29(3):409–13. Additional Declarations No competing interests reported. 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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-4930139","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":346429065,"identity":"6ac587a4-ea86-4a06-aeca-25409d443e98","order_by":0,"name":"Mitra Abbasifard","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mitra","middleName":"","lastName":"Abbasifard","suffix":""},{"id":346429066,"identity":"ef6c23a8-bb64-4b95-9a66-a3fde51dd577","order_by":1,"name":"Kosar Jafarizadeh","email":"","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kosar","middleName":"","lastName":"Jafarizadeh","suffix":""},{"id":346429067,"identity":"728288d5-f461-445f-9a9d-cf65156e4f1d","order_by":2,"name":"Mobina Taghipoor","email":"","orcid":"","institution":"Shiraz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mobina","middleName":"","lastName":"Taghipoor","suffix":""},{"id":346429068,"identity":"a4fc806e-5b15-4706-b11a-fcb1b465f660","order_by":3,"name":"Zahra Bagheri-Hosseinabadi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYDACCQY2MM0GQTZAJmPjAVK0pIG0NBCnBarrMJiFV4v87Aa2Bx/+1MnxSTc/e/Cj7Lzd2vbDQFtqbKJxaWGcc4DdcGbbYWM2mWPmhj3nbidvO5MI1HIsLbcBhxZmiQQ2ad6GA4ltEglmErxtt5PNDgC1MDYcxqmFDaSF509dfZtE+jfJv23nks3OP8SvhQeshY05gU0ix0yat+2AndkNArZIyBxskwT6xbBNIqfcWOZccoLZDaAtCXj8Ij+7+ZgEMMTk5Wekb3v4pszO3ux8+sMHH2pscGoBRRwKNxHMTcCpHAuwJ0XxKBgFo2AUjAwAAOLvXOPnTBenAAAAAElFTkSuQmCC","orcid":"","institution":"Rafsanjan University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zahra","middleName":"","lastName":"Bagheri-Hosseinabadi","suffix":""}],"badges":[],"createdAt":"2024-08-17 14:06:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4930139/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4930139/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":69063707,"identity":"87074fc8-38b6-465d-a119-76dbb6a24851","added_by":"auto","created_at":"2024-11-15 08:17:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":709667,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4930139/v1/85433767-f3af-46a9-a829-b1271e38ab88.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of vitamin D levels with bone density in patients with osteoporosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOsteoporosis, also known as \"brittle bone disease\" or \"porous bone,\" is a skeletal disorder characterized by the deterioration of bone tissue and loss of bone mass. It commonly occurs in old age and is considered the primary cause of bone fractures worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The World Health Organization (WHO) defines osteoporosis as a reduction in bone density of 2.5 standard deviations or more below the average peak bone density in young, healthy individuals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Unlike many chronic diseases that manifest various symptoms, osteoporosis often remains asymptomatic until a bone fracture occurs. It can lead to fractures in different areas of the body, such as the spine, hips, and wrists [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Hip fractures are particularly severe and associated with high mortality rates [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, osteoporosis-related fractures tend to occur in areas that are uncommon in healthy individuals [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Osteoporosis affects both genders, but its prevalence is much higher in women than in men [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The prevalence of the disease varies across different regions, with approximately 200\u0026nbsp;million people worldwide estimated to be affected. In the United States, about 10\u0026nbsp;million individuals have been diagnosed with osteoporosis, and an additional 34\u0026nbsp;million have low bone mass, putting them at risk of developing osteoporosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDiagnosis of osteoporosis is based on clinical history, clinical signs, and bone mass estimation tests [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Radiological evidence can also aid in diagnosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Dual-energy x-ray absorptiometry (DXA) is considered the gold standard for bone mass estimation due to its repeatability, non-invasiveness, short examination time, and minimal radiation exposure. The results are reported as T-scores, with T-score \u0026minus;\u0026thinsp;1 or higher indicating normal bone density, T-score between \u0026minus;\u0026thinsp;1 and \u0026minus;\u0026thinsp;2.5 indicating low bone density (osteopenia), and T-score \u0026minus;\u0026thinsp;2.5 or lower indicating osteoporosis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOsteoporosis is influenced by various factors. With advancing age, bone tissue breakdown exceeds its formation, leading to an increased risk of osteoporosis in older individuals [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Alcohol consumption, smoking, and certain medications, especially glucocorticoids, can also contribute to osteoporosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Other factors such as physical inactivity, weight loss of more than 10% of body weight compared to young adulthood, or a body mass index (BMI) below 19 are associated with an increased risk of osteoporosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, several genetic variations and single nucleotide polymorphisms (SNPs) have been associated with osteoporosis risk. Specific genes involved in bone formation, remodeling, and mineralization have been identified, and certain variations in these genes can influence bone health and increase susceptibility to osteoporosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Vitamin D (VitD) deficiency is another significant factor associated with osteoporosis [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. VitD deficiency is a common nutritional deficiency worldwide, with over 40% of adults over the age of 50 estimated to be deficient [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Deficiency in VitD may impress osteoporosis proneness via impaired calcium absorption, altered bone remodeling, reduced bone mineralization, and reduced bone density [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVitD, a steroid hormone, plays a crucial role in bone mineralization and other metabolic processes, including skeletal growth [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Its main role in bone metabolism is to increase plasma calcium and phosphate levels, which are essential for mineralization. It also promotes proper nerve transmission, neuromuscular junctions, and the secretion of hormones, especially parathyroid hormone (PTH). These mechanisms increase bone mineral density, reducing the risk of osteoporosis and its consequences [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. While a concentration between 50 nmol/L to 125 nmol/L is usually considered as the normal levels of VitD, VitD insufficiency is often defined as having levels between 30 nmol/L and 50 nmol/L, and VitD deficiency is typically defined as having levels below 30 nmol/L [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The status of VitD can vary among individuals in different countries and even within regions of the same country due to physical differences, human race, and environmental factors. Factors such as impaired absorption, limited sunlight exposure, and increased demand for rapid growth can contribute to VitD deficiency. A deficiency in VitD negatively affects calcium metabolism, osteoblastic activity, bone matrix synthesis, bone remodeling, and bone density [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In adults, low VitD levels are associated with osteomalacia, osteopenia, osteoporosis, and related fractures [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Furthermore, observational studies have shown that low 25-hydroxy VitD levels are associated with an increased risk of various non-skeletal diseases, including cancer, infections, autoimmune diseases, and cardiovascular disease (CVD) [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Given the information provided, we sought to determine the serum VitD levels in patients with osteoporosis who visited the Densitometry Center in Rafsanjan city during the first six months of 2022. VitD level assessment plays an important role in diagnosing and managing osteoporosis. We hope that conducting this study will contribute effectively to the prevention of osteoporosis and related complications such as fractures.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy subjects\u003c/h2\u003e \u003cp\u003eThis research was carried out on individuals who were referred to the Densitometry Center of Rafsanjan city, Iran, during the initial half of 2022. A total of 500 patients with osteoporosis and 500 individuals without osteoporosis were selected as the control group.\u003c/p\u003e \u003cp\u003eThe BMD of the participants was measured at the hip, femur neck, and L1-L4 spine while lying on their back using the Stratos device (DMS IMAGING, France) and the DXA method. Based on the WHO's recommended criteria, subjects with a T score less than \u0026minus;\u0026thinsp;2.5 were classified as having osteoporosis, and subjects with a T score greater than \u0026minus;\u0026thinsp;1 were considered part of the control group [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inclusion criteria for the study were as follows: not having conditions, such as liver and kidney failure, thyroid and parathyroid disorders, hematological diseases (such as anemia, thrombocytopenia, leukopenia), malignancies, autoimmune diseases (such as ankylosing spondylitis, rheumatoid arthritis, lupus, etc.), not being pregnant, having no active infections, or blood transfusion in the last year, and not taking medications like bisphosphonates, selective estrogen receptor modulators, denosumab, steroids, and VitD metabolism affecting medications like phenytoin.\u003c/p\u003e \u003cp\u003eFinally, a 5 ml sample of whole blood was collected to assess the serum VitD levels. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline data and biochemical indexes of the participants in the study. The research received approval from the ethics committee of Rafsanjan University of Medical Sciences (IR.RUMS.REC.1401.080), and written informed consent was obtained from all the participants involved in the study.\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 data, demographics, clinical, and laboratory measurements of the study participants.\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=\"left\" 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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOsteoporosis\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-osteoporosis\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;500)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (Year); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male/Female); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (8.8%)/ 456 (91.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (9.8%)/ 451 (90.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCareer status (working/ household); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e388 (77.6%)/ 112 (22.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e394 (78.8%)/ 106 (21.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (married/ single); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e481 (96.2%)/ 19 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e477 (95.4%)/ 23 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (illiterate/ educated); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89 (17.8%)/ 411 (82.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (14.8%)/ 426 (85.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving area (urbane/ rural); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e411 (82.2%)/ 89 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e429 (85.5%)/ 71 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (8.2%)/ 459 (91.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (11.6%)/ 442 (88.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.11\u0026thinsp;\u0026plusmn;\u0026thinsp;5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.13\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenarche age in females (Year); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenopause duration in females (Year); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (cells/mm\u003csup\u003e3\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7439\u0026thinsp;\u0026plusmn;\u0026thinsp;1159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6388\u0026thinsp;\u0026plusmn;\u0026thinsp;1258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count (cells/mm\u003csup\u003e3\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234000\u0026thinsp;\u0026plusmn;\u0026thinsp;23000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e245000\u0026thinsp;\u0026plusmn;\u0026thinsp;16000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.69\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.10\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC count (million cells/mm\u003csup\u003e3\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP (IU/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135.56\u0026thinsp;\u0026plusmn;\u0026thinsp;38.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.50\u0026thinsp;\u0026plusmn;\u0026thinsp;34.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (IU/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.47\u0026thinsp;\u0026plusmn;\u0026thinsp;9.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (IU/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.14\u0026thinsp;\u0026plusmn;\u0026thinsp;8.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.14\u0026thinsp;\u0026plusmn;\u0026thinsp;8.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR (mm/h); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.20\u0026thinsp;\u0026plusmn;\u0026thinsp;5.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBS (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114.6\u0026thinsp;\u0026plusmn;\u0026thinsp;41.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.14\u0026thinsp;\u0026plusmn;\u0026thinsp;24.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.30\u0026thinsp;\u0026plusmn;\u0026thinsp;31.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121.72\u0026thinsp;\u0026plusmn;\u0026thinsp;29.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e114.30\u0026thinsp;\u0026plusmn;\u0026thinsp;31.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105.14\u0026thinsp;\u0026plusmn;\u0026thinsp;28.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117.40\u0026thinsp;\u0026plusmn;\u0026thinsp;28.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105.32\u0026thinsp;\u0026plusmn;\u0026thinsp;27.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.20\u0026thinsp;\u0026plusmn;\u0026thinsp;7.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN (mg/dl); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.34\u0026thinsp;\u0026plusmn;\u0026thinsp;7.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.65\u0026thinsp;\u0026plusmn;\u0026thinsp;7.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D level (nmol/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone fracture history (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (18.2%)/ 409 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (4.2%)/ 479 (95.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSunscreen use (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (23%)/ 385 (77%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 (25.6%)/ 372 (74.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D supplement use (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e392 (78.4%)/ 108 (21.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211 (42.2%)/ 289 (57.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSun exposure duration (hours/day); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidity (diabetes, hypertension) (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (16.2%)/ 419 (83.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (96%)/ 452 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug (anti-hypertension, diabetes) use (yes/ no); n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81 (16.2%)/ 419 (83.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (96%)/ 452 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI; Body-mass index, WBC; White blood cell, RBC; Red blood cell, ALP; Alkaline phosphatase, AST; Aspartate aminotransferase, ALT; Alanine aminotransferase, CRP; C-reactive protein, ESR; Erythrocyte sedimentation rate, FBS; Fasting blood sugar, TC; Total cholesterol, TG; Triglyceride, LDL; Low-density lipoprotein, HDL; High-density lipoprotein, BUN; Blood urea nitrogen, SD; Standard deviation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory measurements\u003c/h2\u003e \u003cp\u003eThe levels of various substances in the blood were assessed through enzymatic colorimetric methods after an overnight fasting. Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase (ALT), Fasting blood sugar (FBS), Triglyceride (TG), Low density lipoprotein (LDL), High density lipoprotein (HDL), Creatinine, and Blood urea nitrogen (BUN) concentrations were determined using these methods. Erythrocyte sedimentation rate (ESR) was measured through the automated kinetic photometric method. Additionally, the level of C-reactive protein (CRP) was measured using the nephelometric method. The count of blood cells and hematologic indices was determined using the complete blood count (CBC) test performed with the Sysmex KX-21N Hematology Analyzer (Sysmex, Japan).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of serum VitD levels\u003c/h2\u003e \u003cp\u003eThe level of VitD in serum samples of study subjects was measured using Enzyme linked immunosorbent assay (ELISA) by a commercial kit (R\u0026amp;D system, USA) based on manufacturer\u0026rsquo;s protocols.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eGraphPad Prism v.9.00 for Windows (La Jolla, CA, USA) was utilized for graph design and statistical comparisons. The normality of quantitative data was assessed using the Shapiro-Wilk test. Group comparisons of non-parametric variables were conducted using the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test. To examine potential correlations between scale variables, the Spearman's correlation test was employed. The study results were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard deviation (SD), and \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u0026rsquo; characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e demonstrates the baseline data, demographics and laboratory data of the study groups. The study participants composed of 44 (8.8%) males and 456 (91.2%) females in the osteoporosis group and 49 (9.8%) males and 451 (90.2%) females in the non-osteoporosis group. The mean age of the osteoporosis and non-osteoporosis groups was 69.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3 and 67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;20.4 years, respectively. There were no statistically significant differences in both the gender distribution and age between the study groups and therefore, the study subjects were matched for age and gender. The hemoglobin concentration was significantly lower in the osteoporosis group in comparison to the non-osteoporosis group. The levels of CRP, ESR, and FBS were significantly higher in the osteoporosis group in comparison to the non-osteoporosis subjects.\u003c/p\u003e \u003cp\u003eHistory of bone fracture was significantly higher in the osteoporosis group [91 (18.2%)] compared to the non-osteoporosis subjects [21 (4.2%)]. Furthermore, the number of cases using VitD supplement was significantly higher in the osteoporosis subjects [392 (78.4%)] in comparison to the non-osteoporosis individuals [211 (42.2%)]. However, sunscreen use and sun exposure were not significantly different between the study groups (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eZ-score, T-score, and BMD\u003c/h2\u003e \u003cp\u003eZ-score and T-score of Hip, Z-score and T-score of spine, and Z-score and T-score of femur were all significantly lower in the osteoporosis patients compared to non-osteoporosis subjects. In addition, BMD of hip, spine, and femur was significantly lower in the osteoporosis group in comparison to the non-osteoporosis group (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\u003eZ-score, T-score, and BMD of hip, spine, and femur in the study groups.\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=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" 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\u003eScoring\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOsteoporosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-osteoporosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score Hip; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-score Hip; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score Spine; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-score Spine; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZ-score Femur; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT-score Femur; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e-2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e-0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpine BMD (g/cm\u003csup\u003e2\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.842\u0026thinsp;\u0026plusmn;\u0026thinsp;0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.342\u0026thinsp;\u0026plusmn;\u0026thinsp;0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHip BMD (g/cm\u003csup\u003e2\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.471\u0026thinsp;\u0026plusmn;\u0026thinsp;0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.281\u0026thinsp;\u0026plusmn;\u0026thinsp;0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemur BMD (g/cm\u003csup\u003e2\u003c/sup\u003e); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.944\u0026thinsp;\u0026plusmn;\u0026thinsp;0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.482\u0026thinsp;\u0026plusmn;\u0026thinsp;0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSD; Standard deviation, BMD; Bone mineral density\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eVitD levels\u003c/h2\u003e \u003cp\u003eIt was detected that VitD level was significantly lower in the osteoporosis cases (31.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.44 nmol/L) compared to the non-osteoporosis subjects (41.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.25 nmol/L) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). VitD level was significantly higher in the male subjects compared to female patients in the osteoporosis group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048), while it was not significantly different between the male and female subjects of the non-osteoporosis subjects (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.128). In both osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) and non-osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) subjects, the level of VitD was significantly lower in the subjects with a history of bone fracture compared to those without a history of bone fracture. Furthermore, in both osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) and non-osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) groups, the level of VitD was significantly lower in the cases using sunscreen compared to those not using sunscreen. In cases using VitD supplement, the level of VitD was significantly higher in both the osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and non-osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) subjects (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eVitamin D level in the study groups based on the specifications of the subjects.\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=\"char\" char=\"\u0026plusmn;\" 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=\"\u0026plusmn;\" 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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eVitamin D level (nmol/L); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOsteoporosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-osteoporosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male/ female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e34.05\u0026thinsp;\u0026plusmn;\u0026thinsp;9.93/ 28.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e42.16\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8/ 41.14\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking (smoker/ non-smoker)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e30.14\u0026thinsp;\u0026plusmn;\u0026thinsp;9.19/ 32.16\u0026thinsp;\u0026plusmn;\u0026thinsp;9.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e40.32\u0026thinsp;\u0026plusmn;\u0026thinsp;10.26/ 42.98\u0026thinsp;\u0026plusmn;\u0026thinsp;10.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCareer status (working/ household)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4/ 31.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.36\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3/ 41.94\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status (married/ single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.26\u0026thinsp;\u0026plusmn;\u0026thinsp;9.58/ 31.04\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e40.66\u0026thinsp;\u0026plusmn;\u0026thinsp;10.11/ 42.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation (illiterate/ educated)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.05\u0026thinsp;\u0026plusmn;\u0026thinsp;9/ 31.25\u0026thinsp;\u0026plusmn;\u0026thinsp;9.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e41.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.29/ 42.08\u0026thinsp;\u0026plusmn;\u0026thinsp;10.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving area (urbane/ rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.89/ 32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.09/ 43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone fracture history (yes/ no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e27.85\u0026thinsp;\u0026plusmn;\u0026thinsp;8.14/ 34.45\u0026thinsp;\u0026plusmn;\u0026thinsp;10.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e39.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.95/ 43.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSunscreen use (yes/ no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.11\u0026thinsp;\u0026plusmn;\u0026thinsp;7.29/ 37.19\u0026thinsp;\u0026plusmn;\u0026thinsp;11.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e37.56\u0026thinsp;\u0026plusmn;\u0026thinsp;8.85/ 45.74\u0026thinsp;\u0026plusmn;\u0026thinsp;11.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D supplement use (yes/ no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e32.76\u0026thinsp;\u0026plusmn;\u0026thinsp;10.11/ 29.54\u0026thinsp;\u0026plusmn;\u0026thinsp;8.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e59.24\u0026thinsp;\u0026plusmn;\u0026thinsp;12.81/ 24.06\u0026thinsp;\u0026plusmn;\u0026thinsp;7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCo-morbidity (yes/ no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.85/ 32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.98\u0026thinsp;\u0026plusmn;\u0026thinsp;9.77/ 44.32\u0026thinsp;\u0026plusmn;\u0026thinsp;10.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug use (yes/ no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e29.59\u0026thinsp;\u0026plusmn;\u0026thinsp;9.11/ 32.71\u0026thinsp;\u0026plusmn;\u0026thinsp;9.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e38.54\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8/ 44.76\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation analysis\u003c/h2\u003e \u003cp\u003eThe correlation analysis was performed between the VitD levels and patients\u0026rsquo; data in the osteoporosis group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). It was seen that the VitD level had significantly positive correlation with the sun exposure duration (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.29, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039). Analysis revealed that VitD level had negative significant correlation with Z-score Hip (\u003cem\u003er\u003c/em\u003e= -0.41, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), T-score Hip (\u003cem\u003er\u003c/em\u003e= -0.55, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), Z-score Spine (\u003cem\u003er\u003c/em\u003e= -0.49, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), T-score Spine (\u003cem\u003er\u003c/em\u003e= -0.48, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), Z-score femur (\u003cem\u003er\u003c/em\u003e= -0.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), and T-score femur (\u003cem\u003er\u003c/em\u003e= -0.59, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) in the osteoporosis patients. The VitD level had significantly positive correlation with the BMD of hip (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.44, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), spine (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.56, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), and femur (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.60, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003eAnalysis of correlation between the Vitamin D level and data of cases with osteoporosis.\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=\"char\" char=\".\" 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=\"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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eVitD level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eVitD level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenarche age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenopause duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.141\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBUN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSun exposure duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ-score Hip; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRBC count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT-score Hip; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ-score Spine; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT-score Spine; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ-score Femur; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eT-score Femur; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.59\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpine BMD; Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-0.54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHip BMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpine BMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.56\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemur BMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.60\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eBMI; Body-mass index, WBC; White blood cell, RBC; Red blood cell, ALP; Alkaline phosphatase, AST; Aspartate aminotransferase, ALT; Alanine aminotransferase, CRP; C-reactive protein, ESR; Erythrocyte sedimentation rate, FBS; Fasting blood sugar, TC; Total cholesterol, TG; Triglyceride, LDL; Low-density lipoprotein, HDL; High-density lipoprotein, BUN; Blood urea nitrogen, BMD; Bone mineral density\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhile there is existing research on the relationship between VitD and bone health, there are gaps and inconclusive observations in the evidence specific to osteoporosis patients in Iranian population. In addition, Osteoporosis prevalence and risk factors can vary across different populations. By focusing on a specific population, we intended to address the relevance of VitD levels to bone health in the context of local genetics, lifestyle, and environmental factors. Hence, we performed this study to determine the serum VitD levels in patients with osteoporosis who visited the Densitometry Center in Rafsanjan city during the first six months of 2022. VitD level assessment plays an important role in diagnosing and managing osteoporosis. Understanding the association between VitD levels and BMD in osteoporosis patients can have significant clinical implications. It may help healthcare professionals develop targeted treatment strategies, such as personalized VitD supplementation, to improve bone health outcomes and prevent further bone loss.\u003c/p\u003e \u003cp\u003eA recent systematic review and meta-analysis research indicated that a combination of VitD and calcium could be able to significantly diminish the risk of fractures in the osteoporotic patients [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Additionally, results of this study emphasized that the positive impact of combination of VitD and calcium supplementation on bone formation remained consistent over a period of three years, providing further evidence of its beneficial effect on bone structure [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In consistent with these observations, our study indicated that level of VitD was lower in the osteoporosis patients. Furthermore, VitD levels had statistically significant correlation with BMD in the hip, spine, and femur.\u003c/p\u003e \u003cp\u003eJavadi \u003cem\u003eet al\u003c/em\u003e. conducted a study in 2003 to evaluate the relationship between calcium and VitD intake, serum calcium and VitD levels, BMD, and osteoporosis in individuals living in Tehran, Iran. Blood sampling was performed in the winter at the participants' residences. The study included 830 participants aged 20 to 76 years, with 39.2% being males and 60.8% females. The study revealed that VitD levels were lower in men compared to women, and serum calcium levels were higher in men. Calcium and VitD intake were higher in men compared to women. The total calcium intake, along with VitD intake, was found to predict serum calcium levels. The study indicated that the dietary intake of calcium in the studied population only covered 50\u0026ndash;60% of the daily requirement, while VitD intake covered approximately 15% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Pourhashem \u003cem\u003eet al\u003c/em\u003e. conducted a study in 2012 to evaluate the prevalence of osteoporosis and its association with serum VitD levels in elderly residents of northern Iran. The study found that the overall prevalence of osteoporosis in at least one site was 32% (28.5% in the lumbar spine and 14.5% in the femoral neck). The prevalence of osteoporosis was 7.55% in women and 4.12% in elderly men. The BMD in the femoral neck showed a negative correlation with age but did not show any significant association with serum VitD levels in the study [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Rahmati \u003cem\u003eet al\u003c/em\u003e. conducted a study in 2016 to assess the prevalence of VitD deficiency among individuals referred to laboratories in the city of Ilam (north of Iran). The study included 2919 participants, of which 70.3% were women. The overall prevalence of VitD deficiency in individuals was estimated to be approximately 62%. Severe and moderate VitD deficiencies were found in 10.4% and 51.5% of the participants, respectively. The prevalence of VitD deficiency in the age groups 1\u0026ndash;6, 7\u0026ndash;18, 19\u0026ndash;60, and above 60 years was 45%, 59%, 64%, and 58%, respectively. The mean serum level of VitD was 36.25\u0026thinsp;\u0026plusmn;\u0026thinsp;18.79 ng/mL. The study also showed a statistically significant association between VitD deficiency and age and gender. The group concluded that the high prevalence of VitD deficiency calls for intervention measures to prevent its consequences, such as pharmaceutical treatment and food enrichment programs to increase VitD intake [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Our research also revealed that VitD levels is lower in the patients with osteoporosis compared to non-osteoporosis subjects. In addition, its level was lower in the female subjects compared to male patients.\u003c/p\u003e \u003cp\u003eIn a study conducted by Papadakis \u003cem\u003eet al\u003c/em\u003e. in 2015 to investigate seasonal changes in serum VitD levels in osteoporosis patients, the serum VitD level was examined in 596 patients (mean age of 65.3 years) at different time intervals over a period of 2.5 years. The findings indicated that the minimum serum level was observed in March, while the maximum levels were recorded in August, September, and October. The prevalence of VitD deficiency and insufficiency in March was 76.5% and 7.8%, respectively. In contrast, the highest prevalence of VitD sufficiency was observed in August, September, and October (38.1%, 45.3%, and 46.5%, respectively), indicating that seasonal variations significantly affect the VitD levels in these patients [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Our research, on the other hand, focused on determining the overall VitD levels in a population of osteoporosis patients and provided an essential baseline understanding of VitD status in this group. While we did not delve into the seasonal variations, it serves as a comprehensive snapshot of the VitD status at a specific point in time, offering valuable data on the general prevalence of VitD deficiency or sufficiency in the population. However, by exploring the relationship between VitD and BMD as well as T-score and Z-score of hip, spine, and femur, our study provides insights into the potential impact of VitD status on bone health in this specific patient group. Understanding this association is vital as VitD plays a key role in calcium absorption and bone metabolism, which directly influences bone density and strength.\u003c/p\u003e \u003cp\u003eIn conclusion, our study findings have demonstrated a significant association between lower VitD levels and reduced BMD in osteoporosis subjects within the Iranian population. Moreover, we observed a higher incidence of bone fractures among individuals with lower VitD levels. The implications of these results in clinical practice are substantial. Healthcare professionals, especially those dealing with osteoporosis patients, should consider VitD assessment as an essential component of their evaluation. Identifying individuals with VitD deficiency or insufficiency can help in early detection and prompt intervention to optimize VitD levels and potentially improve bone health outcomes. As a limitation of this study, we did not include patients with osteopenia, that could have been yielding further insights in the VitD deficiency and BMD and bone fracture. As for further studies, several areas could benefit from additional research. Firstly, longitudinal studies can be conducted to investigate the long-term effects of VitD supplementation on BMD and fracture risk reduction in osteoporosis patients. Such studies can provide more comprehensive data on the sustained impact of VitD interventions over an extended period. Secondly, clinical trials that evaluate the specific dosage and duration of VitD supplementation in osteoporosis patients can help establish evidence-based guidelines for its use. These trials may compare different VitD dosages and examine their effects on BMD, fracture incidence, and overall bone health. Additionally, it would be valuable to investigate the potential interactions between VitD and other factors that influence bone health, such as calcium intake, physical activity, and genetic factors. Understanding these interactions can lead to a more comprehensive approach to osteoporosis management, targeting multiple aspects that contribute to bone health. Furthermore, research focusing on diverse populations and various geographic regions can provide insights into potential variations in VitD status and its association with osteoporosis risk across different demographics and environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved from the local Human Research Ethics Committee located in Rafsanjan University of Medical Sciences (IR.RUMS.REC.1401.080) and written informed consent form was taken by all subjects. All methods were carried out in accordance with relevant guidelines and regulations provided by Rafsanjan University of Medical Sciences. Research carried out here were in compliance with the Helsinki Declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed and generated during the study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMitra Abbasifard, Kosar Jafarizadeh,\u0026nbsp;Mobina Taghipoor, and\u0026nbsp;Zahra Bagheri-Hosseinabadi\u0026nbsp;declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by a grant from the Rafsanjan University of Medical Sciences, Rafsanjan, Iran.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; Contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMA\u003c/strong\u003e; examined the patients, participated in manuscript preparation, and read the manuscript critically.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKJ\u003c/strong\u003e; Contributed in performing the experiments, participated in manuscript preparation and read the manuscript critically.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMT\u003c/strong\u003e; Performed the statistical analysis, participated in manuscript preparation, and read the manuscript critically.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZBH\u003c/strong\u003e; Developed the main idea, Performed the experiments, take the financial support, participated in manuscript preparation and read the manuscript critically.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful of the patients and the healthy individuals for their participation in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRachner TD, Khosla S, Hofbauer LC. Osteoporosis: now and the future. Lancet. 2011;377(9773):1276\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCzerwiński E, Badurski JE, Marcinowska-Suchowierska E, Osieleniec J. Current understanding of osteoporosis according to the position of the World Health Organization (WHO) and International Osteoporosis Foundation. Ortop Traumatol Rehabil. 2007;9(4):337\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026ouml;zen T, \u0026Ouml;zışık L, Başaran N\u0026Ccedil;. An overview and management of osteoporosis. Eur J Rheumatol. 2017;4(1):46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin JT, Lane JM. Osteoporosis: a review. Clinical Orthopaedics and Related Research (1976\u0026ndash;2007). 2004;425:126\u0026thinsp;\u0026ndash;\u0026thinsp;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen G, Chen L, Wen J, Yao J, Li L, Lin L, et al. 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Association between body mass index and osteoporosis in women from northwestern Rio Grande do Sul☆. Revista brasileira de reumatologia. 2017;57:299\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastrogiovanni P, Trovato FM, Szychlinska MA, Nsir H, Imbesi R, Musumeci G. The importance of physical activity in osteoporosis. From the molecular pathways to the clinical evidence. 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosoi T. Genetic aspects of osteoporosis. J Bone Miner Metab. 2010;28:601\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLips P, Van Schoor NM. The effect of vitamin D on bone and osteoporosis. Best Pract Res Clin Endocrinol Metab. 2011;25(4):585\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmrein K, Scherkl M, Hoffmann M, Neuwersch-Sommeregger S, K\u0026ouml;stenberger M, Tmava Berisha A, et al. Vitamin D deficiency 2.0: an update on the current status worldwide. Eur J Clin Nutr. 2020;74(11):1498\u0026ndash;513.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrincat M, Gambin J, Brincat M, Calleja-Agius J. The role of vitamin D in osteoporosis. Maturitas. 2015;80(3):329\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJenkinson C. The vitamin D metabolome: An update on analysis and function. Cell Biochem Funct. 2019;37(6):408\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBikle DD, Vitamin D. Newer concepts of its metabolism and function at the basic and clinical level. J Endocr Soc. 2020;4(2):bvz038.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVoulgaridou G, Papadopoulou SK, Detopoulou P, Tsoumana D, Giaginis C, Kondyli FS, et al. Vitamin D and calcium in osteoporosis, and the role of bone turnover markers: A narrative review of recent data from RCTs. Diseases. 2023;11(1):29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrentice A, Vitamin. D deficiency: a global perspective. Nutr Rev. 2008;66(suppl2):S153\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLakkireddy M, vardhan Mudavath S, Karra ML, Arora AJ. Hypovitaminosis D in patients with osteoporotic hip fractures. J Clin Orthop trauma. 2019;10(4):768\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatyjaszek-Matuszek B, Lenart-Lipińska M, Woźniakowska E. Clinical implications of vitamin D deficiency. Menopause Review/Przegląd Menopauzalny. 2015;14(2):75\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBouillon R, Eelen G, Verlinden L, Mathieu C, Carmeliet G, Verstuyf A. Vitamin D and cancer. J Steroid Biochem Mol Biol. 2006;102(1\u0026ndash;5):156\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanis JA. Diagnosis of osteoporosis and assessment of fracture risk. Lancet. 2002;359(9321):1929\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEleni A, Panagiotis P. A systematic review and meta-analysis of vitamin D and calcium in preventing osteoporotic fractures. Clin Rheumatol. 2020;39(12):3571\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10067-020-05122-3\u003c/span\u003e\u003cspan address=\"10.1007/s10067-020-05122-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePorthouse J, Cockayne S, King C, Saxon L, Steele E, Aspray T, et al. Randomised controlled trial of calcium and supplementation with cholecalciferol (vitamin D3) for prevention of fractures in primary care. BMJ. 2005;330(7498):1003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHossein-nezhad A, Khalili-Fard A, Maghbooli J. Correlation between bone mineral density and osteoporosis With Ca and vitamin D intake. Zahedan J Res Med Sci. 2003;5(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePourhashem Z, Bayani M, Noreddini H, Bijani A, Hosseini SR. Prevalence of osteoporosis and its association with serum vitamin D level in older people in Amirkola, North of Iran. Caspian J Intern Med. 2012;3(1):347.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahmati S, Yadegarazadi A, Shamloo B, Rabiei Fakhr F, Azami M, Borji M, et al. The frequency of vitamin d deficiency among referred to clinical laboratories in Eyvan city during 2015 and 2016-Ilam province. Iran SSU_Journals. 2016;24(3):261\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapadakis G, Keramidas I, Kakava K, Pappa T, Villiotou V, Triantafillou E, et al. Seasonal variation of serum vitamin D among Greek female patients with osteoporosis. vivo. 2015;29(3):409\u0026ndash;13.\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":"Vitamin D, Osteoporosis, Bone mineral density, Bone fracture","lastPublishedDoi":"10.21203/rs.3.rs-4930139/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4930139/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOsteoporosis is a prevalent skeletal disorder characterized by reduced bone mass and deterioration of bone microarchitecture, leading to an increased risk of fractures. Given the growing recognition of the association between vitamin D (VitD) and bone health, there is a pressing need to conduct studies focusing on the level of VitD and its correlation with bone mineral density (BMD) in osteoporosis patients. This study aims to address this critical knowledge gap by exploring the association between VitD levels and bone mineral density in osteoporosis patients from an Iranian population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe recruited 500 subjects with osteoporosis and 500 non-osteoporosis cases. The BMD of the cases was measured in the hip, femur neck, and L1-L4 spine using the Stratos device via DXA method. VitD level was measured in the serum of study participants using ELISA.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eVitD level was significantly lower in the osteoporosis cases (31.15\u0026thinsp;\u0026plusmn;\u0026thinsp;9.44 nmol/L) compared to the non-osteoporosis subjects (41.65\u0026thinsp;\u0026plusmn;\u0026thinsp;10.25 nmol/L). It was significantly higher in the male subjects compared to female patients in the osteoporosis group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.048). In both osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) and non-osteoporosis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) subjects, the level of VitD was significantly lower in the subjects with a history of bone fracture compared to those without a history of bone fracture. The VitD level had significantly positive correlation with the BMD of hip (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.44, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), spine, and femur.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eVitD deficiency in the osteoporosis patients is associated with BMD and bone fractures.\u003c/p\u003e","manuscriptTitle":"Association of vitamin D levels with bone density in patients with osteoporosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-24 19:19:06","doi":"10.21203/rs.3.rs-4930139/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":"e6fd376b-d5a8-435a-acf6-3e6090891fc4","owner":[],"postedDate":"September 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-15T08:08:58+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-24 19:19:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4930139","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4930139","identity":"rs-4930139","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}