25-hydroxy vitamin D levels associated with cardiovascular risk factors among military personnel based on obesity status

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Obesity and vitamin D deficiency both affect each other. Many obese individuals exhibit a combination of metabolic and cardiovascular risk factors. Methods The present study was conducted cross-sectional in 2023. The study population was considered to be 216 military personnel from Tehran. Blood samples were taken from the subjects to measure high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), fasting blood sugar (FBS), and 25-hydroxy vitamin D. Height, weight, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse were also measured. Using a questionnaire, demographic information and information about the history of some diseases were collected from the study subjects. Results The mean age was 41.06 years, and the mean work experience was 8.02 years. A higher percentage of diabetic or pre-diabetic subjects were obese or overweight (p < 0.001). The average level of very low-density lipoprotein (VLDL) in subjects with normal weight was 27.23 times lower than other subjects. In normal-weight subjects in the study, there was a negative association between 25-hydroxyvitamin D and DBP (β= -0.061). Conclusion We discovered a significant link between 25-hydroxyvitamin D insufficiency in military personnel and heightened cardiovascular risk factors. Subsequent studies employing a longitudinal approach are necessary to validate our results and shed more light on the influence of vitamin D on cardiovascular risk. Earth and environmental sciences/Environmental sciences Health sciences/Risk factors Cardiovascular Military Personnel 25-hydroxyvitamin D Figures Figure 1 1. Introduction Cardiovascular diseases were responsible for nearly one-third of total deaths worldwide in 2016. It is predicted that cardiovascular diseases will be the cause of over 23 million deaths globally by 2030 ( 1 , 2 ). Risk factors such as body mass index (BMI), systolic blood pressure, low-density lipoprotein cholesterol, and diabetes constitute a percentage of the prevalence and occurrence of cardiovascular diseases ( 3 ). The Global Burden of Disease group has estimated that elevated BMI levels were associated with 4 million deaths in 2015, with two-thirds of these attributed to cardiovascular diseases ( 4 ). Type 2 diabetes is a major risk factor for cardiovascular diseases, and there is an association between obesity and type 2 diabetes. Since obesity is often accompanied by high blood pressure and dyslipidemia, many high-risk patients with obesity exhibit a set of metabolic and cardiovascular risk factors ( 5 ). Obesity and 25-hydroxyvitamin D deficiency both affect each other. In recent years, the amount of studies investigating the role of 25-hydroxyvitamin D in biological pathways has been increasing ( 6 ). 25-hydroxyvitamin D deficiency has been associated with an increased risk of diabetes, arterial hypertension, heart failure, peripheral arterial disease, autoimmune and inflammatory diseases, immunodeficiency, and increased mortality ( 7 ). Also, 25-hydroxyvitamin D plays an essential role in the regulation of glucose homeostasis, mechanisms of insulin secretion, and obesity-related inflammation ( 8 ). 25-hydroxyvitamin D is a prohormone essential for skeletal and muscular health, the natural immune system, and various other bodily functions ( 9 ). It has recently been proven to play a role in immunity and cardiovascular health as well ( 10 ). Dobnig et al related low 25-hydroxyvitamin D levels in a cohort of subjects scheduled for angiography to increased all-cause and CV mortality ( 11 ). Studies have shown that the risk of developing heart failure increases in individuals with a deficiency in 25-hydroxyvitamin D ( 10 ). Additionally, 25-hydroxyvitamin D deficiency is associated with an increase in blood pressure ( 12 ). A significant negative correlation was found in a study between 25-hydroxyvitamin D levels and systolic blood pressure ( 13 ). Another study indicated that obesity could reduce the effectiveness of 25-hydroxyvitamin D supplementation in obese patients, with serum 25-hydroxyvitamin D concentrations in obese individuals being 17.38 nanomoles per liter less than those with normal weight ( 14 ). It is generally believed that military personnel undergo vigorous sports and high-intensity physical training and have a lower prevalence of metabolic syndrome and hyperuricemia. Although the results of epidemiological studies show that the capacity for exercise and physical training is higher in military people, the risk factors for cardiovascular and metabolic diseases are not lower than in the general population ( 15 ). Despite weight and fitness standards for military personnel, these individuals are not immune to the obesity epidemic and its associated health effects. Studies have shown that soldiers gain as much weight each year as civilians ( 16 ). Military forces play a crucial role in defending, maintaining the security, and ensuring the stability of a nation. These individuals are significantly exposed to various injuries and specific diseases due to their missions, duties, and occupational requirements ( 17 ). Many of these conditions, upon occurrence, require regular and continuous medical care, and controlling the factors leading to them can be challenging in military settings ( 18 ). Low 25-hydroxyvitamin D status is common in individuals engaged in regular intense physical activity, especially when accompanied by psychological stress, insufficient nutrition, or sleep disorders ( 19 ). This places military personnel in a high-risk category, with significant negative consequences for their health ( 19 ). Therefore, considering the importance of the health of military personnel, this study aimed to investigate the relationship between 25-hydroxyvitamin D levels and cardiovascular risk factors, taking into account the obesity status of individuals, among military personnel in Tehran in 2023. 2. Materials and Methods 2.1. Study population The present study was conducted cross-sectionally in 2023. The study population was considered to be 216 military personnel from Tehran. All procedures performed in studies involving human participants were in accordance with institutional committee ethical standards (all methods were performed in accordance with the relevant guidelines to this effect). This study has been approved by the Ethics Committee of Baqiyatullah Educational and Medical Center. The ethical approval code is IR.BMSU.BAQ.REC.1402.119. the experimental protocols were approved by a Baqiyatullah Educational and Medical Center committee. Written informed consent was obtained from all subjects. At least 2 ml of blood samples were taken from the study subjects in the fasting state for blood lipid profile tests, including the measurement of high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), Fasting blood sugar (FBS) and 25-hydroxyvitamin D were measured. Blood samples were collected in test tubes containing EDTA anticoagulant. Blood tests were performed using a Hitachi 704 autoanalyzer (Hitachi, Tokyo, Japan) ( 20 ). Physical examinations including measurement of height, weight, body mass index (BMI), systolic blood pressure (SBP) diastolic blood pressure (DBP), and pulse were taken from the subjects. subjects weight was measured with little clothes and without shoes using a digital scale. The individual's height was determined by measuring from the points on the body (back of the head, hips, and heels) touching the wall with a meter. Additionally, the body mass index was computed by dividing the weight in kilograms by the square of the height in meters. Blood pressure and pulse measurements were obtained while sitting using a digital blood pressure monitor on the right hand. Classification for obesity variables is as follows: a BMI below 24 kg/m2 is considered normal, a BMI ranging from 25 to 29 kg/m2 is classified as overweight, and a BMI exceeding 30 kg/m2 falls under the category of obesity ( 21 ). Using a questionnaire, demographic information including age (in years), work experience (in years), marital status (single or married), as well as information related to allergy history, history of hospitalization and family illness history, history of drug use, cardiovascular diseases were taken from the studied subjects ( 20 ). 2.2. Statistical analysis To examine the relationship between quantitative variables across different obesity groups, the Analysis of Variance (ANOVA) test was employed. Furthermore, the frequency discrepancy among qualitative variables with obesity groups was assessed using the chi-squared (χ2) test. Subsequently, univariate linear regression analyses (or Logestic) were conducted to examine the relationship between all variables and 25-hydroxyvitamin D levels by univariate linear regression separately in the obesity group. All statistical analyses were performed using R version 4.3.2 software, and a significance level of 95% was adopted for all tests. 3. Results In Table 1 , the associations between demographic factors and disease history with obesity status are presented. The mean age of the subjects in the study was 41.06 years, and their mean work experience amounted to 8.02 years. Notably, the study exclusively consisted of male subjects. The mean age of obese subjects was higher than other subjects (p = 0.012). A significant relationship between the absence of lung disease was observed in overweight and obese subjects more than other subjects (p = 0.006). A significant relationship between the absence of allergies was observed in subjects with overweight and obesity more than other subjects (p = 0.013). Table 1 Demographic factors and disease history with obesity status variables Total Mean ± SD P-value Normal Overweight Obese Age 41.06 ± 7.90 38.77 ± 8.45 41.96 ± 7.18 42.51 ± 7.93 0.012 Work Experience 8.02 ± 6.804 7.01 ± 6.31 8.72 ± 7.28 8.02 ± 6.41 0.280 Frequency n(%) Marital Status married 184(85.2) 53(28.8) 87(47.3) 44(23.9) 0.059 Single 32(14.8) 16(50.0) 11(34.4) 5(15.6) Disease Background Yes 46(21.3) 12(26.1) 21(45.7) 13(28.3) 0.489 No 170(78.7) 57(33.5) 77(45.3) 36(21.2) Hospitalization History Yes 14(6.5) 5(35.7) 5(35.7) 4(28.6) 0.740 No 202(93.5) 64(31.7) 93(46.0) 45(22.3) family health history Yes 90(41.7) 26(28.9) 42(46.7) 22(24.4) 0.698 No 126(58.3) 43(34.1) 56(44.4) 27(21.4) History of drug use Yes 26(12.0) 6(23.1) 13(50.0) 7(26.9) 0.577 No 190(88.0) 63(33.2) 85(44.7) 42(22.1) Lung Condition Normal 193(89.4) 62(32.1) 93(48.2) 38(19.7) 0.006 Unnormal 23(10.6) 7(30.4) 5(21.7) 11(47.8) Allergy Yes 20(9.3) 12(60.0) 4(20.0) 4(20.0) 0.013 No 196(90.7) 57(29.1) 94(48.0) 45(23.0) Heart Condition Normal 202(93.5) 64(31.7) 92(45.5) 46(22.8) 0.952 Unnormal 14(6.5) 5(35.7) 6(42.9) 3(21.4) Table 2 shows the relationship between demographic factors and disease history with the level of 25 hydroxyvitamin D based on obesity status. The results showed that the average level of 25 hydroxyvitamin D in obese subjects who took medicine was 9.219 times higher than other subjects who took medicine. Table 2 Relationship between demographic factors and disease history with 25-hydroxyvitamin D level according to obesity status Variables Total Normal Overweight Obese β (SE) Age (Year) 0.126(0.04) 0.091(0.012) 0.124(0.13) 0.041(0.14) Work Experience -0.018(0.08) 0.025(0.16) -0.118(0.13) -0.024(0.17) Marital Status (Married) 2.654(1.65) 2.949(2.30) 2.887(2.88) 3.864(3.52) Disease Background (Yes) 1.570(1.43) -0.023(2.62) -1.152(2.23) 3.842(2.38) Allergy (Yes) -0.930(2.02) -0.679(2.62) -1.231(2.28) 4.443(3.88) Hospitalization History (Yes) -1.897(2.38) -7.965(3.71) -1.919(4.16) 3.001(3.91) family health history (Yes) 0.771(1.19) 0.122(2.05) 0.537(1.85) 1.639(2.15) Taking Medication (Yes) 3.900(1.78) * 2.325(3.52) 0.971(2.70) 9.219(2.78) * Lung Condition (Normal) 0.321(1.88) 1.605(3.28) 1.645(4.16) -0.872(2.58) Heart Condition (Normal) -5.443(7.01) -4.865(3.79) -5.701(3.78) -2.483(4.48) a.Univariate Linear Regression * p-value is significant at the 0.05 level. Table 3 shows the cardiovascular risk factors according to obesity status. Subjects in the study with normal weight exhibited mean very-low-density lipoprotein (VLDL) levels of 27.23, which were lower than the values in other subjects (p = 0.004). A higher percentage of diabetic or pre-diabetic subjects were obese or overweight (p < 0.001). Table 3 Cardiovascular risk factors according to obesity status variables Normal Overweight Obese P-value Mean ± SD Pulse 75.17 ± 5.00 76.85 ± 11.69 76.71 ± 12.22 0.801 LDL 99.67 ± 35.45 96.58 ± 35.28 102.38 ± 36.95 0.635 HDL 44.21 ± 8.24 41.22 ± 10.37 44.30 ± 8.63 0.062 VLDL 27.23 ± 13.12 34.01 ± 13.90 32.84 ± 11.92 0.004 Frequency n(%) Diabetes Normal 67(33.3) 94(46.8) 40(19.9) < 0.001 Prediabetes 2(15.4) 2(15.4) 9(69.2) Diabetes 0 2(100) 0 SBP l 49(36.3) 56(41.5) 30(22.2) 0.186 High 20(24.7) 42(51.9) 19(23.5) DBP Normal 53(32.7) 70(43.2) 39(24.1) 0.512 High 16(29.6) 28(51.9) 10(18.5) TC Normal 66(32.8) 91(45.3) 44(21.9) 0.469 High 3(20.0) 7(46.7) 5(33.3) TG Normal 57(35.4) 69(42.9) 35(21.7) 0.174 High 12(21.8) 29(52.7) 14(25.5) a. ANOVA or Chi-square Table 4 shows the relationship between 25-hydroxyvitamin D and cardiovascular risk factors based on obesity status. In normal-weight subjects in the study, there was a negative association between 25-hydroxyvitamin D and DBP ( \(\beta =-0.061\) ). An increase in the level of 25-hydroxyvitamin D has decreased cholesterol, but this relationship is not significant in Obese subjects. Table 4 Relationship between 25-hydroxyvitamin D and cardiovascular Risk factors according to obesity status Variables Total Normal Overweight Obese SBP -0.022(0.02) -0.044(0.03) -0.023(0.02) 0.021(0.04) DBP -0.011(0.02) -0.061(0.03)* 0.004(0.02) 0.034(0.05) Diabetes -0.022(000) -0.142(0.14) -0.091(0.27) 0.010(0.05) TC -0.877(0.31)* -1.119(0.56)* -0.987(0.42)* -0.435(0.76) TG -0.927(0.68) -1.616(1.06) -1.44(1.08) 0.887(1.07) LDL -0.267(0.28) -0.581(0.51) -0.90(0.39) -0.267(0.69) HDL -0.035(0.08) 0.017(0.12) -0.027(0.11) -0.12(0.16) VLDL -0.051(0.12) -0.249(0.19) -0.047(0.15) 0.110(0.23) Pulse -0.089(0.13) -0.024(0.16) -0.157(0.23) -0.049(0.23) a. Univariate Linear Regression/Logistic Regression * p-value is significant at the 0.05 level. According to Fig. 1, the difference in mean 25-hydroxyvitamin D levels in obese status was not significant (p = 0.080). None of the subjects lost weight. 4. Discussion 25-hydroxyvitamin D is significantly known to prevent cardiovascular diseases through its effect on the immune system of subjects. The prognosis associated with the epidemic of 25-hydroxyvitamin D deficiency is still poorly understood. However, successive reports of the association of 25-hydroxyvitamin D with various cardiovascular diseases have been of great interest ( 22 ). In our study, the prevalence of obesity is higher among the subjects who were older, with increasing age, mobility, and physical activity decrease, which is one of the reasons for obesity ( 23 ). Some studies have shown that an increase in BMI decreases the average serum 25-hydroxyvitamin D level ( 24 ), while in our study this relationship is not significant. Considering that the subjects examined in our study are all the personnel who participated in the annual monitoring, maybe the reason why it is not significant is that the 25-hydroxyvitamin D treatment was suggested to them by the doctor. In our study, the average uric acid, and VLDL of obese subjects is higher than other subjects, and the prevalence of diabetes in obese subjects was higher than other personnel. Obesity is associated with excessive production of uric acid and poor excretion due to insulin resistance, which leads to impaired uric acid metabolism ( 25 ). Dyslipidemia, manifested by decreased HDL and increased triglycerides, is associated with obesity. There is evidence that shows that dyslipidemia can still occur in the absence of insulin resistance in obesity ( 26 ). According to Russian studies, compared to subjects with a normal profession, military personnel as representatives of a dangerous job, due to excessive exposure to psycho-emotional stress, had a significantly higher prevalence of metabolic syndrome ( 27 ). Severe anxiety, stress, and nervous system weakness are important factors in causing carbohydrate metabolism disorders. The importance of this factor is indirectly proven by the higher frequency of diagnosis of components of metabolic syndrome and insulin resistance in people who are exposed to severe psycho-emotional effects ( 28 ). The daily dose of 25-hydroxyvitamin D consumed may vary from 10 to 100 µg depending on the individual ( 29 ). In our study, the relationship between the average level of 25-hydroxyvitamin D and the status of taking medication is not significant in general, but it is significant only in obese subjects, as mentioned before, because our study was conducted on employees who receive continuous medical care, probably the dose The consumption of obese subjects has been more than other subjects. In our study, there was a negative association between 25-hydroxyvitamin D and DBP in normal-weight subjects in the study. Many observational and laboratory studies support the notion that 25-hydroxyvitamin D has a protective effect against the development of hypertension. A seasonal variation in blood pressure was recognized, with lower values in the summer and higher in the winter period, when UV light exposure and circulating 25OHD concentrations were lower. In the large cross-sectional study representative of United States (US) civilians, an inverse relationship between 25(OH)D levels and blood pressure after adjusting for age, sex, ethnicity, and physical activity was shown ( 30 ). 25-hydroxyvitamin D was shown to reduce cholesterol accumulation in macrophages and LDL uptake in atheroma ( 31 ). In addition, it affects platelet aggregation and thrombogenic activity ( 30 ). This study confirmed the results of our research, in our study, increasing the level of 25-hydroxyvitamin D decreased TC, but this relationship was not significant in obese subjects. 25-hydroxyvitamin D may directly affect lipid levels and adipogenesis or indirectly affect parathyroid hormone and calcium homeostasis. 25-hydroxyvitamin D may be transported by lipoproteins because 25-hydroxyvitamin D-binding proteins have been observed on lipoproteins, especially very low-density lipoproteins. Therefore, it is plausible that circulating levels of lipoproteins influence free 25(OH)D levels ( 32 ). 5. Conclusion Both obesity and 25-hydroxyvitamin D interact. Recently, studies have shown that 25-hydroxyvitamin D levels play a role in heart health. Considering that in recent years, the amount of studies that examine the role of 25-hydroxyvitamin D in biological pathways is increasing, it is important to conduct more studies on specific groups. Also, contrary to public opinion, the risk of hospital and metabolic diseases in the subjects is not less than in the general population and may be higher due to stressful situations, this puts military personnel in the high-risk category. Our study, which was conducted on a special group of military personnel, by other researchers, shows that the relationship between 25-hydroxyvitamin D and cardiovascular risk factors is significant, and this relationship is higher in some factors in obese or overweight subjects. These results show the importance of health monitoring focusing on 25-hydroxyvitamin D levels and cardiovascular risk factors, especially in military personnel. Declarations Acknowledgements The authors express their thanks and gratitude to the research assistant at Baqiyatullah Educational and Therapeutic Center. Ethical Approval The present study has the code of ethics IR.BMSU.BAQ.REC.1402.119 of Baqiyatullah educational and therapeutic center . Consent to Participate All procedures performed in studies involving human participants were in accordance with institutional committee ethical standards. This study has been approved by the Ethics Committee of Baqiyatullah Educational and Medical Center. The ethical approval code is IR.BMSU.BAQ.REC.1402.119. Written informed consent was obtained from all subjects. Consent to Publish Not applicable. Data Availability Statement The supporting data are available from the corresponding authors upon reasonable request. Authors Contributions All authors contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by M.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, and M.R . The first draft of the manuscript was written by M.E and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript. Conceptualization was performed by M.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, M.R ; Methodology by M.E, H.A, M.R ; Formal analysis and investigation by M.E, H.A, M.K, M.I, M.R ; Writing-original draft preparation by M.E, S.M, M.N, H.N, Writing-review and editing by M.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, M.R . Funding No funding was received to assist with the preparation of this manuscript. Competing Interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Amini M, Zayeri F, Salehi M. Trend analysis of cardiovascular disease mortality, incidence, and mortality-to-incidence ratio: results from global burden of disease study 2017. BMC Public Health. 2021;21(1):1–12. Sanjari M, Amirkhosravi L, Hosseini SE, Abdollahi F, Maghfoori A, Eghbalian M. Underweight, overweight, obesity and associated factors among elementary school children: A cross-sectional study in Kerman province, Iran. Obesity Medicine. 2023;38:100477. Consortium GCR. Global effect of modifiable risk factors on cardiovascular disease and mortality. New England Journal of Medicine. 2023;389(14):1273–85. Hay S, Collaborators GBoDO. Health effects of overweight and obesity in 195 countries over 25 years. New England journal of medicine. 2017;377. Piché M-E, Tchernof A, Després J-P. Obesity phenotypes, diabetes, and cardiovascular diseases. Circulation research. 2020;126(11):1477–500. Roth CL, Elfers C, Kratz M, Hoofnagle AN. Vitamin D deficiency in obese children and its relationship to insulin resistance and adipokines. Journal of obesity. 2011;2011. Reis A, Hauache O, Velho G. Vitamin D endocrine system and the genetic susceptibility to diabetes, obesity and vascular disease. A review of evidence. Diabetes & metabolism. 2005;31(4):318–25. Hyppönen E, Power C. Vitamin D status and glucose homeostasis in the 1958 British birth cohort: the role of obesity. Diabetes care. 2006;29(10):2244–6. Žmitek K, Hribar M, Lavriša Ž, Hristov H, Kušar A, Pravst I. Socio-demographic and knowledge-related determinants of vitamin D supplementation in the context of the COVID-19 pandemic: assessment of an educational intervention. Frontiers in nutrition. 2021;8:648450. Roffe-Vazquez DN, Huerta-Delgado AS, Castillo EC, Villarreal-Calderón JR, Gonzalez-Gil AM, Enriquez C, et al. Correlation of vitamin D with inflammatory cytokines, atherosclerotic parameters, and lifestyle factors in the setting of heart failure: a 12-month follow-up study. International Journal of Molecular Sciences. 2019;20(22):5811. Dobnig H, Pilz S, Scharnagl H, Renner W, Seelhorst U, Wellnitz B, et al. Independent association of low serum 25-hydroxyvitamin D and 1, 25-dihydroxyvitamin D levels with all-cause and cardiovascular mortality. Archives of internal medicine. 2008;168(12):1340–9. Cosentino N, Campodonico J, Milazzo V, De Metrio M, Brambilla M, Camera M, et al. Vitamin D and cardiovascular disease: current evidence and future perspectives. Nutrients. 2021;13(10):3603. Joukar F, Naghipour M, Hassanipour S, Salari A, Alizadeh A, Saeidi-Saedi H, et al. Association of serum levels of Vitamin D with blood pressure status in Northern Iranian population: the PERSIAN Guilan Cohort Study (PGCS). International journal of general medicine. 2020:99–104. Bennour I, Haroun N, Sicard F, Mounien L, Landrier J-F. Vitamin D and Obesity/Adiposity—A Brief Overview of Recent Studies. Nutrients. 2022;14(10):2049. Liu C-W, Chang W-C, Lee C-C, Chen K-H, Wu Y-W, Hwang J-J. Hyperuricemia is associated with a higher prevalence of metabolic syndrome in military individuals. Military medicine. 2018;183(11–12):e391-e5. Funderburk LK, Arsenault JE. Prevalence of abnormal serum lipids among overweight and obese soldiers. Military Medicine. 2013;178(10):1137–40. Raeeszadeh M, Goodarzi H, Moghaddam JA, Machian MSB, Gooshki HS, Khoshi A. The role of military medicine and the significance of training military medicine. J Family Med Prim Care. 2022;11(8):4184–9. Campbell P, Pope R, Simas V, Canetti E, Schram B, Orr R. The Effects of Early Physiotherapy Treatment on Musculoskeletal Injury Outcomes in Military Personnel: A Narrative Review. International Journal of Environmental Research and Public Health. 2022;19(20):13416. McCarthy MS, Elshaw EB, Szekely BM, Raju D. A prospective cohort study of vitamin D supplementation in AD soldiers: preliminary findings. Military Medicine. 2019;184(Supplement_1):498–505. Nasab H, Rajabi S, Eghbalian M, Malakootian M, Hashemi M, Mahmoudi-Moghaddam H. Association of As, Pb, Cr, and Zn urinary heavy metals levels with predictive indicators of cardiovascular disease and obesity in children and adolescents. Chemosphere. 2022;294:133664. Hashemi M, Rajabi S, Eghbalian M, Suliburska J, Nasab H. Demographic and anthropometric characteristics and their effect on the concentration of heavy metals (arsenic, lead, chromium, zinc) in children and adolescents. Heliyon. 2023;9(2). Anderson JL, May HT, Horne BD, Bair TL, Hall NL, Carlquist JF, et al. Relation of vitamin D deficiency to cardiovascular risk factors, disease status, and incident events in a general healthcare population. The American journal of cardiology. 2010;106(7):963–8. Li B, Li Y, Zhang Y, Liu P, Song Y, Zhou Y, et al. Visceral fat obesity correlates with frailty in middle-aged and older adults. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2022:2877–84. Lenders CM, Feldman HA, Von Scheven E, Merewood A, Sweeney C, Wilson DM, et al. Relation of body fat indexes to vitamin D status and deficiency among obese adolescents. The American journal of clinical nutrition. 2009;90(3):459–67. Li F, Chen S, Qiu X, Wu J, Tan M, Wang M. Serum uric acid levels and metabolic indices in an obese population: A cross-sectional study. Diabetes, Metabolic Syndrome and Obesity. 2021:627–35. Segula D. Complications of obesity in adults: a short review of the literature. Malawi Medical Journal. 2014;26(1):20–4. YuB K, Patsenko M, Osh O. Degree of manifestation of metabolic syndrome and of lipid metabolism disorders in people in hazardous occupations. Disaster Medicine. 2016;(2 (94)): 19–21. Russ. Petrankov KV, Salukhov VV, Pugachev MI, Dobrovolskaya LM, Alexandrova AV, Shipilova DA, et al. Prognostic assessment of risk factors for type 2 diabetes mellitus in young military personnel. Bulletin of the Russian Military Medical Academy. 2022;24(2):277–87. Wakeman M. A literature review of the potential impact of medication on vitamin D status. Risk management and healthcare policy. 2021:3357–81. Latic N, Erben RG. Vitamin D and cardiovascular disease, with emphasis on hypertension, atherosclerosis, and heart failure. International journal of molecular sciences. 2020;21(18):6483. Yin K, You Y, Swier V, Tang L, Radwan MM, Pandya AN, et al. Vitamin D protects against atherosclerosis via regulation of cholesterol efflux and macrophage polarization in hypercholesterolemic swine. Arteriosclerosis, thrombosis, and vascular biology. 2015;35(11):2432–42. Hiserote A, Berry-Cabán C, Wu Q, Wentz L. Correlations between vitamin D concentrations and lipid panels in active duty and veteran military personnel. Int J Sports Exerc Med. 2016;2:034. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4638076","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":327783877,"identity":"d73f807a-648a-448d-8a05-6bd54aa314ce","order_by":0,"name":"Mostafa Eghbalian","email":"","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mostafa","middleName":"","lastName":"Eghbalian","suffix":""},{"id":327783878,"identity":"f7f60997-f0a5-4598-816f-595c635e087f","order_by":1,"name":"Hesam Akbari","email":"","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hesam","middleName":"","lastName":"Akbari","suffix":""},{"id":327783879,"identity":"d496646a-1598-4732-82ec-b17c2ccca241","order_by":2,"name":"Saeideh Moradalizadeh","email":"","orcid":"","institution":"Kerman University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Saeideh","middleName":"","lastName":"Moradalizadeh","suffix":""},{"id":327783880,"identity":"d8470fb0-281a-40d5-96a7-d738ec300a54","order_by":3,"name":"Mojtaba Norouzi","email":"","orcid":"","institution":"Kerman University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mojtaba","middleName":"","lastName":"Norouzi","suffix":""},{"id":327783881,"identity":"d8893d7d-319d-4b16-8440-b2fd4df8c965","order_by":4,"name":"Habibeh Nasab","email":"","orcid":"","institution":"Shahid Sadoughi University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Habibeh","middleName":"","lastName":"Nasab","suffix":""},{"id":327783882,"identity":"c0d5dd0e-28be-438d-8153-d65a86cae17e","order_by":5,"name":"Mazyar Karamali","email":"","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mazyar","middleName":"","lastName":"Karamali","suffix":""},{"id":327783883,"identity":"bd47edd7-2ee2-4697-a17a-871dc66058f1","order_by":6,"name":"Mousa Imani","email":"","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mousa","middleName":"","lastName":"Imani","suffix":""},{"id":327783884,"identity":"c9d26d24-7131-4ade-89e3-b1cfa4c85c78","order_by":7,"name":"Hossein Zahiri","email":"","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hossein","middleName":"","lastName":"Zahiri","suffix":""},{"id":327783885,"identity":"fb01a207-0b3c-4e6b-a3bf-3898c68a7c8f","order_by":8,"name":"Mehdi Raei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFACHgaJBBB9vIGBmUQtZw6QogVM30ggUotue+/BGw8Y7jHw3Xxj+LmgwoaBv707Aa8WszPnki0SGIoZJG/nGEvPOJPGIHHm7Ab8Wm7kmAH9ksBgcDvHQJq37TCDgUQuAS3330C13Dxj/Js4LTd4oFqADCJtOZNjbAHSInkmrcya50waD2G/HD9jePMHUAvf8cObb/NU2Mjxt/fi1wIGjP8Y6hsYOAxAbB7CyhGA/QEpqkfBKBgFo2AEAQBlCEQRxITotAAAAABJRU5ErkJggg==","orcid":"","institution":"Baqiyatallah University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Mehdi","middleName":"","lastName":"Raei","suffix":""}],"badges":[],"createdAt":"2024-06-25 17:27:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4638076/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4638076/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60911706,"identity":"4fce3d18-b4df-4bf9-a436-f39e47eab91a","added_by":"auto","created_at":"2024-07-23 12:59:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":133352,"visible":true,"origin":"","legend":"\u003cp\u003e25-hydroxyvitamin D level according to obesity status\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4638076/v1/6145baf4d2e118b02d11d230.png"},{"id":70096008,"identity":"675c923f-ef05-40af-9681-8f872333699d","added_by":"auto","created_at":"2024-11-28 09:39:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":853379,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4638076/v1/e6998ba4-33ac-498c-bddb-a6f53a2194b9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"25-hydroxy vitamin D levels associated with cardiovascular risk factors among military personnel based on obesity status","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCardiovascular diseases were responsible for nearly one-third of total deaths worldwide in 2016. It is predicted that cardiovascular diseases will be the cause of over 23\u0026nbsp;million deaths globally by 2030 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Risk factors such as body mass index (BMI), systolic blood pressure, low-density lipoprotein cholesterol, and diabetes constitute a percentage of the prevalence and occurrence of cardiovascular diseases (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The Global Burden of Disease group has estimated that elevated BMI levels were associated with 4\u0026nbsp;million deaths in 2015, with two-thirds of these attributed to cardiovascular diseases (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eType 2 diabetes is a major risk factor for cardiovascular diseases, and there is an association between obesity and type 2 diabetes. Since obesity is often accompanied by high blood pressure and dyslipidemia, many high-risk patients with obesity exhibit a set of metabolic and cardiovascular risk factors (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eObesity and 25-hydroxyvitamin D deficiency both affect each other. In recent years, the amount of studies investigating the role of 25-hydroxyvitamin D in biological pathways has been increasing (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). 25-hydroxyvitamin D deficiency has been associated with an increased risk of diabetes, arterial hypertension, heart failure, peripheral arterial disease, autoimmune and inflammatory diseases, immunodeficiency, and increased mortality (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Also, 25-hydroxyvitamin D plays an essential role in the regulation of glucose homeostasis, mechanisms of insulin secretion, and obesity-related inflammation (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e25-hydroxyvitamin D is a prohormone essential for skeletal and muscular health, the natural immune system, and various other bodily functions (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). It has recently been proven to play a role in immunity and cardiovascular health as well (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Dobnig et al related low 25-hydroxyvitamin D levels in a cohort of subjects scheduled for angiography to increased all-cause and CV mortality (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Studies have shown that the risk of developing heart failure increases in individuals with a deficiency in 25-hydroxyvitamin D (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Additionally, 25-hydroxyvitamin D deficiency is associated with an increase in blood pressure (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). A significant negative correlation was found in a study between 25-hydroxyvitamin D levels and systolic blood pressure (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Another study indicated that obesity could reduce the effectiveness of 25-hydroxyvitamin D supplementation in obese patients, with serum 25-hydroxyvitamin D concentrations in obese individuals being 17.38 nanomoles per liter less than those with normal weight (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is generally believed that military personnel undergo vigorous sports and high-intensity physical training and have a lower prevalence of metabolic syndrome and hyperuricemia. Although the results of epidemiological studies show that the capacity for exercise and physical training is higher in military people, the risk factors for cardiovascular and metabolic diseases are not lower than in the general population (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Despite weight and fitness standards for military personnel, these individuals are not immune to the obesity epidemic and its associated health effects. Studies have shown that soldiers gain as much weight each year as civilians (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMilitary forces play a crucial role in defending, maintaining the security, and ensuring the stability of a nation. These individuals are significantly exposed to various injuries and specific diseases due to their missions, duties, and occupational requirements (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Many of these conditions, upon occurrence, require regular and continuous medical care, and controlling the factors leading to them can be challenging in military settings (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLow 25-hydroxyvitamin D status is common in individuals engaged in regular intense physical activity, especially when accompanied by psychological stress, insufficient nutrition, or sleep disorders (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This places military personnel in a high-risk category, with significant negative consequences for their health (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Therefore, considering the importance of the health of military personnel, this study aimed to investigate the relationship between 25-hydroxyvitamin D levels and cardiovascular risk factors, taking into account the obesity status of individuals, among military personnel in Tehran in 2023.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study population\u003c/h2\u003e \u003cp\u003eThe present study was conducted cross-sectionally in 2023. The study population was considered to be 216 military personnel from Tehran. All procedures performed in studies involving human participants were in accordance with institutional committee ethical standards (all methods were performed in accordance with the relevant guidelines to this effect). This study has been approved by the Ethics Committee of Baqiyatullah Educational and Medical Center. The ethical approval code is IR.BMSU.BAQ.REC.1402.119. the experimental protocols were approved by a Baqiyatullah Educational and Medical Center committee. Written informed consent was obtained from all subjects. At least 2 ml of blood samples were taken from the study subjects in the fasting state for blood lipid profile tests, including the measurement of high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), Fasting blood sugar (FBS) and 25-hydroxyvitamin D were measured. Blood samples were collected in test tubes containing EDTA anticoagulant. Blood tests were performed using a Hitachi 704 autoanalyzer (Hitachi, Tokyo, Japan) (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePhysical examinations including measurement of height, weight, body mass index (BMI), systolic blood pressure (SBP) diastolic blood pressure (DBP), and pulse were taken from the subjects. subjects weight was measured with little clothes and without shoes using a digital scale. The individual's height was determined by measuring from the points on the body (back of the head, hips, and heels) touching the wall with a meter. Additionally, the body mass index was computed by dividing the weight in kilograms by the square of the height in meters. Blood pressure and pulse measurements were obtained while sitting using a digital blood pressure monitor on the right hand. Classification for obesity variables is as follows: a BMI below 24 kg/m2 is considered normal, a BMI ranging from 25 to 29 kg/m2 is classified as overweight, and a BMI exceeding 30 kg/m2 falls under the category of obesity (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUsing a questionnaire, demographic information including age (in years), work experience (in years), marital status (single or married), as well as information related to allergy history, history of hospitalization and family illness history, history of drug use, cardiovascular diseases were taken from the studied subjects (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Statistical analysis\u003c/h2\u003e \u003cp\u003eTo examine the relationship between quantitative variables across different obesity groups, the Analysis of Variance (ANOVA) test was employed. Furthermore, the frequency discrepancy among qualitative variables with obesity groups was assessed using the chi-squared (χ2) test. Subsequently, univariate linear regression analyses (or Logestic) were conducted to examine the relationship between all variables and 25-hydroxyvitamin D levels by univariate linear regression separately in the obesity group. All statistical analyses were performed using R version 4.3.2 software, and a significance level of 95% was adopted for all tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eIn Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the associations between demographic factors and disease history with obesity status are presented. The mean age of the subjects in the study was 41.06 years, and their mean work experience amounted to 8.02 years. Notably, the study exclusively consisted of male subjects. The mean age of obese subjects was higher than other subjects (p\u0026thinsp;=\u0026thinsp;0.012). A significant relationship between the absence of lung disease was observed in overweight and obese subjects more than other subjects (p\u0026thinsp;=\u0026thinsp;0.006). A significant relationship between the absence of allergies was observed in subjects with overweight and obesity more than other subjects (p\u0026thinsp;=\u0026thinsp;0.013).\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\u003eDemographic factors and disease history with obesity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eOverweight\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eObese\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.06\u0026thinsp;\u0026plusmn;\u0026thinsp;7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.77\u0026thinsp;\u0026plusmn;\u0026thinsp;8.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.51\u0026thinsp;\u0026plusmn;\u0026thinsp;7.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWork Experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.02\u0026thinsp;\u0026plusmn;\u0026thinsp;6.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.01\u0026thinsp;\u0026plusmn;\u0026thinsp;6.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.72\u0026thinsp;\u0026plusmn;\u0026thinsp;7.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.02\u0026thinsp;\u0026plusmn;\u0026thinsp;6.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.280\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\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFrequency n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003emarried\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184(85.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87(47.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44(23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSingle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32(14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(15.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDisease Background\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21(45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13(28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170(78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(33.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77(45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36(21.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHospitalization History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202(93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64(31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93(46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45(22.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003efamily health history\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90(41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26(28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42(46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22(24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126(58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56(44.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27(21.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHistory of drug use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26(12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.577\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e190(88.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63(33.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85(44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42(22.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eLung Condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193(89.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62(32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93(48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38(19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUnnormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23(10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11(47.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAllergy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196(90.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57(29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94(48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45(23.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHeart Condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202(93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64(31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92(45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e46(22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eUnnormal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(35.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(21.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the relationship between demographic factors and disease history with the level of 25 hydroxyvitamin D based on obesity status. The results showed that the average level of 25 hydroxyvitamin D in obese subjects who took medicine was 9.219 times higher than other subjects who took medicine.\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\u003eRelationship between demographic factors and disease history with 25-hydroxyvitamin D level according to obesity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eβ (SE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (Year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.126(0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.091(0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.124(0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041(0.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWork Experience\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.018(0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.025(0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.118(0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.024(0.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status (Married)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.654(1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.949(2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.887(2.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.864(3.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisease Background (Yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.570(1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.023(2.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.152(2.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.842(2.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAllergy (Yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.930(2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.679(2.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.231(2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.443(3.88)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospitalization History (Yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.897(2.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.965(3.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.919(4.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.001(3.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003efamily health history (Yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.771(1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.122(2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.537(1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.639(2.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTaking Medication (Yes)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.900(1.78) *\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.325(3.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.971(2.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.219(2.78) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLung Condition (Normal)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.321(1.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.605(3.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.645(4.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.872(2.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeart Condition (Normal)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.443(7.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.865(3.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-5.701(3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-2.483(4.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ea.Univariate Linear Regression\u003c/p\u003e \u003cp\u003e\u003cb\u003e*\u003c/b\u003e p-value is significant at the 0.05 level.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the cardiovascular risk factors according to obesity status. Subjects in the study with normal weight exhibited mean very-low-density lipoprotein (VLDL) levels of 27.23, which were lower than the values in other subjects (p\u0026thinsp;=\u0026thinsp;0.004). A higher percentage of diabetic or pre-diabetic subjects were obese or overweight (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eCardiovascular risk factors according to obesity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003evariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.17\u0026thinsp;\u0026plusmn;\u0026thinsp;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.85\u0026thinsp;\u0026plusmn;\u0026thinsp;11.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.71\u0026thinsp;\u0026plusmn;\u0026thinsp;12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.67\u0026thinsp;\u0026plusmn;\u0026thinsp;35.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.58\u0026thinsp;\u0026plusmn;\u0026thinsp;35.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102.38\u0026thinsp;\u0026plusmn;\u0026thinsp;36.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.21\u0026thinsp;\u0026plusmn;\u0026thinsp;8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.30\u0026thinsp;\u0026plusmn;\u0026thinsp;8.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVLDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.23\u0026thinsp;\u0026plusmn;\u0026thinsp;13.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.01\u0026thinsp;\u0026plusmn;\u0026thinsp;13.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.84\u0026thinsp;\u0026plusmn;\u0026thinsp;11.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFrequency n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67(33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94(46.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40(19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrediabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(69.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003el\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49(36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(41.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30(22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42(51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(23.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70(43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39(24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28(51.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91(45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44(21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.469\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(33.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57(35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69(42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35(21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14(25.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ea. ANOVA or Chi-square\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the relationship between 25-hydroxyvitamin D and cardiovascular risk factors based on obesity status. In normal-weight subjects in the study, there was a negative association between 25-hydroxyvitamin D and DBP (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\beta =-0.061\\)\u003c/span\u003e\u003c/span\u003e). An increase in the level of 25-hydroxyvitamin D has decreased cholesterol, but this relationship is not significant in Obese subjects.\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\u003eRelationship between 25-hydroxyvitamin D and cardiovascular Risk factors according to obesity status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.022(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.044(0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.023(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021(0.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDBP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.011(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.061(0.03)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034(0.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.022(000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.142(0.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.091(0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010(0.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.877(0.31)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.119(0.56)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.987(0.42)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.435(0.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.927(0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.616(1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.44(1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.887(1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.267(0.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.581(0.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.90(0.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.267(0.69)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.035(0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.017(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.027(0.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.12(0.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVLDL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.051(0.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.249(0.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.047(0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.110(0.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.089(0.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.024(0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.157(0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.049(0.23)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ea. Univariate Linear Regression/Logistic Regression\u003c/p\u003e \u003cp\u003e\u003cb\u003e*\u003c/b\u003e p-value is significant at the 0.05 level.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to Fig.\u0026nbsp;1, the difference in mean 25-hydroxyvitamin D levels in obese status was not significant (p\u0026thinsp;=\u0026thinsp;0.080). None of the subjects lost weight.\u003c/p\u003e "},{"header":"4. Discussion","content":"\u003cp\u003e25-hydroxyvitamin D is significantly known to prevent cardiovascular diseases through its effect on the immune system of subjects. The prognosis associated with the epidemic of 25-hydroxyvitamin D deficiency is still poorly understood. However, successive reports of the association of 25-hydroxyvitamin D with various cardiovascular diseases have been of great interest (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our study, the prevalence of obesity is higher among the subjects who were older, with increasing age, mobility, and physical activity decrease, which is one of the reasons for obesity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Some studies have shown that an increase in BMI decreases the average serum 25-hydroxyvitamin D level (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), while in our study this relationship is not significant. Considering that the subjects examined in our study are all the personnel who participated in the annual monitoring, maybe the reason why it is not significant is that the 25-hydroxyvitamin D treatment was suggested to them by the doctor.\u003c/p\u003e \u003cp\u003eIn our study, the average uric acid, and VLDL of obese subjects is higher than other subjects, and the prevalence of diabetes in obese subjects was higher than other personnel. Obesity is associated with excessive production of uric acid and poor excretion due to insulin resistance, which leads to impaired uric acid metabolism (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Dyslipidemia, manifested by decreased HDL and increased triglycerides, is associated with obesity. There is evidence that shows that dyslipidemia can still occur in the absence of insulin resistance in obesity (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). According to Russian studies, compared to subjects with a normal profession, military personnel as representatives of a dangerous job, due to excessive exposure to psycho-emotional stress, had a significantly higher prevalence of metabolic syndrome (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Severe anxiety, stress, and nervous system weakness are important factors in causing carbohydrate metabolism disorders. The importance of this factor is indirectly proven by the higher frequency of diagnosis of components of metabolic syndrome and insulin resistance in people who are exposed to severe psycho-emotional effects (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe daily dose of 25-hydroxyvitamin D consumed may vary from 10 to 100 \u0026micro;g depending on the individual (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In our study, the relationship between the average level of 25-hydroxyvitamin D and the status of taking medication is not significant in general, but it is significant only in obese subjects, as mentioned before, because our study was conducted on employees who receive continuous medical care, probably the dose The consumption of obese subjects has been more than other subjects.\u003c/p\u003e \u003cp\u003eIn our study, there was a negative association between 25-hydroxyvitamin D and DBP in normal-weight subjects in the study. Many observational and laboratory studies support the notion that 25-hydroxyvitamin D has a protective effect against the development of hypertension. A seasonal variation in blood pressure was recognized, with lower values in the summer and higher in the winter period, when UV light exposure and circulating 25OHD concentrations were lower. In the large cross-sectional study representative of United States (US) civilians, an inverse relationship between 25(OH)D levels and blood pressure after adjusting for age, sex, ethnicity, and physical activity was shown (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e25-hydroxyvitamin D was shown to reduce cholesterol accumulation in macrophages and LDL uptake in atheroma (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In addition, it affects platelet aggregation and thrombogenic activity (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This study confirmed the results of our research, in our study, increasing the level of 25-hydroxyvitamin D decreased TC, but this relationship was not significant in obese subjects.\u003c/p\u003e \u003cp\u003e25-hydroxyvitamin D may directly affect lipid levels and adipogenesis or indirectly affect parathyroid hormone and calcium homeostasis. 25-hydroxyvitamin D may be transported by lipoproteins because 25-hydroxyvitamin D-binding proteins have been observed on lipoproteins, especially very low-density lipoproteins. Therefore, it is plausible that circulating levels of lipoproteins influence free 25(OH)D levels (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eBoth obesity and 25-hydroxyvitamin D interact. Recently, studies have shown that 25-hydroxyvitamin D levels play a role in heart health. Considering that in recent years, the amount of studies that examine the role of 25-hydroxyvitamin D in biological pathways is increasing, it is important to conduct more studies on specific groups. Also, contrary to public opinion, the risk of hospital and metabolic diseases in the subjects is not less than in the general population and may be higher due to stressful situations, this puts military personnel in the high-risk category. Our study, which was conducted on a special group of military personnel, by other researchers, shows that the relationship between 25-hydroxyvitamin D and cardiovascular risk factors is significant, and this relationship is higher in some factors in obese or overweight subjects. These results show the importance of health monitoring focusing on 25-hydroxyvitamin D levels and cardiovascular risk factors, especially in military personnel.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their thanks and gratitude to the research assistant at Baqiyatullah Educational and Therapeutic Center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study has the code of ethics IR.BMSU.BAQ.REC.1402.119\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eof Baqiyatullah educational and therapeutic center\u003cspan dir=\"RTL\"\u003e.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with institutional committee ethical standards. This study has been approved by the Ethics Committee of Baqiyatullah Educational and Medical Center. The ethical approval code is IR.BMSU.BAQ.REC.1402.119. Written informed consent was obtained from all subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe supporting data are available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study\u0026apos;s conception and design. Material preparation, data collection, and analysis were performed by\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eM.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, and M.R\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe first draft of the manuscript was written by \u003cstrong\u003eM.E\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript. Conceptualization was performed by \u003cstrong\u003eM.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, M.R\u003c/strong\u003e; Methodology by \u003cstrong\u003eM.E, H.A, M.R\u003c/strong\u003e; Formal analysis and investigation by \u003cstrong\u003eM.E, H.A, M.K, M.I, M.R\u003c/strong\u003e; Writing-original draft preparation by \u003cstrong\u003eM.E, S.M, M.N, H.N,\u003c/strong\u003e Writing-review and editing by \u003cstrong\u003eM.E, H.A, S.M, M.N, H.N, M.K, M.I, H.Z, M.R\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received to assist with the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAmini M, Zayeri F, Salehi M. Trend analysis of cardiovascular disease mortality, incidence, and mortality-to-incidence ratio: results from global burden of disease study 2017. BMC Public Health. 2021;21(1):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanjari M, Amirkhosravi L, Hosseini SE, Abdollahi F, Maghfoori A, Eghbalian M. Underweight, overweight, obesity and associated factors among elementary school children: A cross-sectional study in Kerman province, Iran. Obesity Medicine. 2023;38:100477.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConsortium GCR. Global effect of modifiable risk factors on cardiovascular disease and mortality. New England Journal of Medicine. 2023;389(14):1273\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHay S, Collaborators GBoDO. Health effects of overweight and obesity in 195 countries over 25 years. New England journal of medicine. 2017;377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePich\u0026eacute; M-E, Tchernof A, Despr\u0026eacute;s J-P. Obesity phenotypes, diabetes, and cardiovascular diseases. Circulation research. 2020;126(11):1477\u0026ndash;500.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoth CL, Elfers C, Kratz M, Hoofnagle AN. Vitamin D deficiency in obese children and its relationship to insulin resistance and adipokines. Journal of obesity. 2011;2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReis A, Hauache O, Velho G. Vitamin D endocrine system and the genetic susceptibility to diabetes, obesity and vascular disease. A review of evidence. Diabetes \u0026amp; metabolism. 2005;31(4):318\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHypp\u0026ouml;nen E, Power C. Vitamin D status and glucose homeostasis in the 1958 British birth cohort: the role of obesity. Diabetes care. 2006;29(10):2244\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eŽmitek K, Hribar M, Lavriša Ž, Hristov H, Kušar A, Pravst I. Socio-demographic and knowledge-related determinants of vitamin D supplementation in the context of the COVID-19 pandemic: assessment of an educational intervention. Frontiers in nutrition. 2021;8:648450.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoffe-Vazquez DN, Huerta-Delgado AS, Castillo EC, Villarreal-Calder\u0026oacute;n JR, Gonzalez-Gil AM, Enriquez C, et al. Correlation of vitamin D with inflammatory cytokines, atherosclerotic parameters, and lifestyle factors in the setting of heart failure: a 12-month follow-up study. International Journal of Molecular Sciences. 2019;20(22):5811.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDobnig H, Pilz S, Scharnagl H, Renner W, Seelhorst U, Wellnitz B, et al. Independent association of low serum 25-hydroxyvitamin D and 1, 25-dihydroxyvitamin D levels with all-cause and cardiovascular mortality. Archives of internal medicine. 2008;168(12):1340\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCosentino N, Campodonico J, Milazzo V, De Metrio M, Brambilla M, Camera M, et al. Vitamin D and cardiovascular disease: current evidence and future perspectives. Nutrients. 2021;13(10):3603.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoukar F, Naghipour M, Hassanipour S, Salari A, Alizadeh A, Saeidi-Saedi H, et al. Association of serum levels of Vitamin D with blood pressure status in Northern Iranian population: the PERSIAN Guilan Cohort Study (PGCS). International journal of general medicine. 2020:99\u0026ndash;104.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBennour I, Haroun N, Sicard F, Mounien L, Landrier J-F. Vitamin D and Obesity/Adiposity\u0026mdash;A Brief Overview of Recent Studies. Nutrients. 2022;14(10):2049.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C-W, Chang W-C, Lee C-C, Chen K-H, Wu Y-W, Hwang J-J. Hyperuricemia is associated with a higher prevalence of metabolic syndrome in military individuals. Military medicine. 2018;183(11\u0026ndash;12):e391-e5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFunderburk LK, Arsenault JE. Prevalence of abnormal serum lipids among overweight and obese soldiers. Military Medicine. 2013;178(10):1137\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaeeszadeh M, Goodarzi H, Moghaddam JA, Machian MSB, Gooshki HS, Khoshi A. The role of military medicine and the significance of training military medicine. J Family Med Prim Care. 2022;11(8):4184\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell P, Pope R, Simas V, Canetti E, Schram B, Orr R. The Effects of Early Physiotherapy Treatment on Musculoskeletal Injury Outcomes in Military Personnel: A Narrative Review. International Journal of Environmental Research and Public Health. 2022;19(20):13416.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCarthy MS, Elshaw EB, Szekely BM, Raju D. A prospective cohort study of vitamin D supplementation in AD soldiers: preliminary findings. Military Medicine. 2019;184(Supplement_1):498\u0026ndash;505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNasab H, Rajabi S, Eghbalian M, Malakootian M, Hashemi M, Mahmoudi-Moghaddam H. Association of As, Pb, Cr, and Zn urinary heavy metals levels with predictive indicators of cardiovascular disease and obesity in children and adolescents. Chemosphere. 2022;294:133664.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHashemi M, Rajabi S, Eghbalian M, Suliburska J, Nasab H. Demographic and anthropometric characteristics and their effect on the concentration of heavy metals (arsenic, lead, chromium, zinc) in children and adolescents. Heliyon. 2023;9(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson JL, May HT, Horne BD, Bair TL, Hall NL, Carlquist JF, et al. Relation of vitamin D deficiency to cardiovascular risk factors, disease status, and incident events in a general healthcare population. The American journal of cardiology. 2010;106(7):963\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi B, Li Y, Zhang Y, Liu P, Song Y, Zhou Y, et al. Visceral fat obesity correlates with frailty in middle-aged and older adults. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 2022:2877\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLenders CM, Feldman HA, Von Scheven E, Merewood A, Sweeney C, Wilson DM, et al. Relation of body fat indexes to vitamin D status and deficiency among obese adolescents. The American journal of clinical nutrition. 2009;90(3):459\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi F, Chen S, Qiu X, Wu J, Tan M, Wang M. Serum uric acid levels and metabolic indices in an obese population: A cross-sectional study. Diabetes, Metabolic Syndrome and Obesity. 2021:627\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSegula D. Complications of obesity in adults: a short review of the literature. Malawi Medical Journal. 2014;26(1):20\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuB K, Patsenko M, Osh O. Degree of manifestation of metabolic syndrome and of lipid metabolism disorders in people in hazardous occupations. Disaster Medicine. 2016;(2 (94)): 19\u0026ndash;21. Russ.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetrankov KV, Salukhov VV, Pugachev MI, Dobrovolskaya LM, Alexandrova AV, Shipilova DA, et al. Prognostic assessment of risk factors for type 2 diabetes mellitus in young military personnel. Bulletin of the Russian Military Medical Academy. 2022;24(2):277\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWakeman M. A literature review of the potential impact of medication on vitamin D status. Risk management and healthcare policy. 2021:3357\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLatic N, Erben RG. Vitamin D and cardiovascular disease, with emphasis on hypertension, atherosclerosis, and heart failure. International journal of molecular sciences. 2020;21(18):6483.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYin K, You Y, Swier V, Tang L, Radwan MM, Pandya AN, et al. Vitamin D protects against atherosclerosis via regulation of cholesterol efflux and macrophage polarization in hypercholesterolemic swine. Arteriosclerosis, thrombosis, and vascular biology. 2015;35(11):2432\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHiserote A, Berry-Cab\u0026aacute;n C, Wu Q, Wentz L. Correlations between vitamin D concentrations and lipid panels in active duty and veteran military personnel. Int J Sports Exerc Med. 2016;2:034.\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":"Cardiovascular, Military Personnel, 25-hydroxyvitamin D","lastPublishedDoi":"10.21203/rs.3.rs-4638076/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4638076/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVitamin D is an essential prohormone for body functions. Obesity and vitamin D deficiency both affect each other. Many obese individuals exhibit a combination of metabolic and cardiovascular risk factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was conducted cross-sectional in 2023. The study population was considered to be 216 military personnel from Tehran. Blood samples were taken from the subjects to measure high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC), fasting blood sugar (FBS), and 25-hydroxy vitamin D. Height, weight, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse were also measured. Using a questionnaire, demographic information and information about the history of some diseases were collected from the study subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age was 41.06 years, and the mean work experience was 8.02 years. A higher percentage of diabetic or pre-diabetic subjects were obese or overweight (p \u0026lt; 0.001). The average level of very low-density lipoprotein (VLDL) in subjects with normal weight was 27.23 times lower than other subjects. In normal-weight subjects in the study, there was a negative association between 25-hydroxyvitamin D and DBP (β= -0.061).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe discovered a significant link between 25-hydroxyvitamin D insufficiency in military personnel and heightened cardiovascular risk factors. Subsequent studies employing a longitudinal approach are necessary to validate our results and shed more light on the influence of vitamin D on cardiovascular risk.\u003c/p\u003e","manuscriptTitle":"25-hydroxy vitamin D levels associated with cardiovascular risk factors among military personnel based on obesity status","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-23 12:59:07","doi":"10.21203/rs.3.rs-4638076/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":"7cade51a-3f1c-43e2-9636-f3bcf1172bc5","owner":[],"postedDate":"July 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34693712,"name":"Earth and environmental sciences/Environmental sciences"},{"id":34693713,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-11-28T09:39:00+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-23 12:59:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4638076","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4638076","identity":"rs-4638076","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}