Multivariate Regression Analysis of Risk Factors for Lower Extremity Varicose Veins Based on VCSS Scores

Multivariate Regression Analysis of Risk Factors for Lower Extremity Varicose Veins Based on VCSS Scores | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Multivariate Regression Analysis of Risk Factors for Lower Extremity Varicose Veins Based on VCSS Scores Yuanxuan Zhang, Duntao Lv, Qiang Li, Ke Zhang, Ning Wei This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7318976/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Objective This study aimed to compare the characteristics of risk factors for lower limb varicose veins (VV) and identify key variables associated with disease severity to guide clinical prevention and management strategies. Methods A cross-sectional study was conducted on 751 patients with primary lower limb varicose veins admitted to the Affiliated Hospital of Xuzhou Medical University between June 2024 and June 2025. Clinical data were collected, and disease severity was assessed using the Venous Clinical Severity Score (VCSS). A Generalized Additive Model (GAM) was applied to analyze the association between VCSS scores and various risk factors, including age, gender, BMI, family history, hypertension, diabetes, smoking, alcohol consumption, behavioral factors, and venous valve dysfunction. Residual analysis was performed to assess model fit. Results Age, gender, BMI, family history, hypertension, diabetes, smoking, alcohol use, behavioral factors, and valve dysfunction were all significantly associated with VCSS scores (all P < 0.05). Female patients showed a slightly higher prevalence than males. Patients who smoked (β = 1.14) or consumed alcohol (β = 1.47) had higher VCSS scores. Obesity was also a major aggravating factor. Chronic diseases such as hypertension (β = 1.45) and diabetes (β = 1.20) increased the disease burden. Valve dysfunction (β = 1.50) had a considerable impact on VCSS scores. The strongest associations were observed for family history (β = 3.13) and behavioral factors (β = 2.04), highlighting the importance of early behavioral intervention and genetic risk management. Conclusions The severity of primary lower limb varicose veins is influenced by a range of risk factors. Clinical management strategies should take these into account, with targeted interventions. For instance, patients with behavioral risk factors may benefit from early use of compression stockings to prevent venous edema, while those with high BMI or a history of smoking should be advised to adopt weight reduction and smoking cessation programs promptly. Varicose veins Risk factors Venous Clinical Severity Score Epidemiology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Chronic venous disease of the lower extremities, including varicose veins, is a common condition with a rising global prevalence. In its early and intermediate stages, superficial varicose veins can adversely affect patients’ quality of life to varying degrees. In advanced stages, the disease may lead to partial loss of work capacity, consume substantial medical resources, and impose significant physical and psychological burdens on patients [ 1 ] . Early manifestations include limb heaviness and discomfort, tortuous and dilated superficial veins. As the disease progresses, symptoms such as pruritus, skin pigmentation, desquamation, lipodermatosclerosis, and even ulceration, hemorrhage, or thrombophlebitis may occur [ 2 ] . Accurate assessment of disease severity is therefore essential for early intervention and individualized treatment planning. The Venous Clinical Severity Score (VCSS) encompasses ten evaluation items, including venous symptoms, varicosities, venous edema, skin pigmentation, inflammatory changes, induration, number and duration of active ulcers, ulcer size, and use of compression therapy [ 3 ] . As a standardized tool for assessing clinical severity, the VCSS is instrumental in guiding clinical decision-making. Multiple international studies have identified age, female sex, taller stature, obesity, pregnancy, and family history as risk factors for varicose veins. However, findings on other factors, such as hypertension, smoking, and obesity-related indices, have been inconsistent [ 4 ] . Notably, most prior studies focused on predominantly White or relatively younger populations. This study utilizes a Generalized Additive Model (GAM) to systematically analyze the risk factors associated with primary lower extremity varicose vein severity in a domestic patient cohort, aiming to clarify the contribution of each factor to disease progression and provide theoretical support for prevention and treatment strategies. Materials and Methods 1. Study Population:A total of 751 patients with a confirmed diagnosis of primary lower extremity varicose veins by ultrasound or digital subtraction angiography (DSA) were enrolled at the Affiliated Hospital of Xuzhou Medical University between June 2024 and June 2025. Patient data, including height, weight, smoking and alcohol history, behavioral factors, medical history, and quality of life, were extracted from hospital admission records. 2. Research Instruments:The severity of varicose veins was assessed using the standardized Venous Clinical Severity Score (VCSS). Demographic characteristics, medical history, and lifestyle factors were also recorded. 3. Statistical Analysis:Data were analyzed using R software. A Generalized Additive Model (GAM) was employed to identify significant risk factors. Results were presented in the form of a forest plot, along with confidence intervals and P-values. 4. Inclusion Criteria:Patients who completed relevant examinations and were diagnosed with primary lower extremity varicose veins via ultrasound or DSA imaging after admission, with complete and reliable clini cal data.Exclusion Criteria:Patients with secondary varicose veins due to other causes, such as Budd-Chiari syndrome or iliac vein compression syndrome; patients who had received any form of surgical or medical treatment prior to admission; or patients with incomplete or inaccurate data. Results To explore the associations between clinical variables and VCSS scores, a Generalized Additive Model (GAM) was employed to account for potential nonlinear effects of age and BMI. The model demonstrated a good fit, with an adjusted R² of 0.820 and an explained deviance of 82.5%. The analysis revealed significant nonlinear relationships between both age and BMI with VCSS scores. Specifically, the smooth term for age had an estimated degrees of freedom (edf) of 7.31 (F = 5.94, p < 0.05), indicating a flexible, nonlinear association with the score. BMI also exhibited a significant nonlinear effect (edf = 4.13, F = 20.63, p < 0.05). Regarding linear parameters, male patients had slightly lower scores than females (β = -0.411, standard error = 0.131, p < 0.05). Several binary clinical factors were significantly associated with increased VCSS scores, including family history (β = 3.13, p < 0.05), hypertension (β = 1.45, p < 0.05), diabetes (β = 1.20, p < 0.05), smoking (β = 1.14, p < 0.05), alcohol consumption (β = 1.47, p < 0.05), behavioral risk factors (β = 2.02, p < 0.05), and valvular insufficiency (β = 1.50, p < 0.05). Table 1 . These results show that all listed factors were significantly associated with higher VCSS scores, with family history and behavioral risk factors showing the strongest effects. Table 1 summarizes the associations between each factor and the VCSS score as determined by the GAM model. Variable Estimate Standard Error t Value P Value Gender (male) -0.411 0.131 -3.134 < 0.05 Family history 3.125 0.164 19.028 < 0.05 Hypertension 1.453 0.178 8.155 < 0.05 Diabetes 1.203 0.295 4.077 < 0.05 Smoking 1.140 0.155 7.378 < 0.05 Alcohol consumption 1.466 0.171 8.567 < 0.05 Behavioral risk factor 2.023 0.141 14.393 < 0.05 Valvular insufficiency 1.497 0.155 9.686 < 0.05 Table 2 . This table indicates that both age and BMI exhibit significant nonlinear associations with VCSS scores in the GAM model. Table 2 Analysis of Nonlinear Effects of Age and BMI in the GAM Model . Nonlinear Variable Estimated Degrees of Freedom (edf) Reference Degrees of Freedom (Ref.df) F Value P Value Age 7.314 8.310 5.942 < 0.05 BMI 4.130 5.119 20.625 < 0.05 Family history suggests a genetic predisposition, while behavioral risk factors show a strong influence on VCSS scores. Valvular insufficiency directly affects hemodynamics. Gender differences may be attributed to the protective role of estrogen and variations in lipid metabolism. In clinical evaluation and intervention, particular attention should be paid to patients with a positive family history, unhealthy lifestyles, and valvular dysfunction. Additionally, differences in score sensitivity by gender should be considered. This finding aligns with previous international studies and suggests that obesity induces chronic inflammation, insulin resistance, and lipid metabolism disorders, which collectively accelerate the progression of chronic diseases, as reflected in the sharp increase in VCSS scores. Patients with a BMI over 27 should be classified as high-risk and targeted for intensified intervention. BMI control strategies should focus on preventing surpassing this risk threshold. This pattern may be due to a combination of factors in older adults, such as atherosclerosis, endothelial dysfunction, and immunosenescence, contributing to a significant rise in scores. In contrast, compensatory mechanisms may still be active in middle-aged individuals, resulting in more stable score changes. Risk assessment should not rely solely on age groupings but should account for the sharp increase in risk among the elderly, supporting early intervention strategies. This phenomenon may be explained by the higher likelihood of visceral fat accumulation, chronic inflammation, and hormonal dysregulation in obese women. These factors may synergistically drive a rapid rise in VCSS scores. In clinical risk assessments and interventions, special attention should be paid to women with high BMI, as their scores are more sensitive to BMI increases. Gender-specific intervention strategies are recommended. This statistical pattern suggests possible threshold effects in the influence of BMI and age on disease progression—risks may increase markedly or plateau beyond certain thresholds. Thus, linear models may not fully capture these pathophysiological dynamics and may fail to accurately predict risk scores, especially for patients at very high or very low risk. In clinical practice, pure linear models should be used cautiously, and more flexible statistical models—such as GAM—are recommended for risk assessment. Discussion In this study, all identified factors significantly influenced VCSS scores. The following interpretations are based on these findings: Age showed a nonlinear relationship with VCSS scores, with scores rising rapidly after age 50, indicating a higher risk in older patients. This is consistent with findings from the Bonn Vein Study, which identified age as an independent risk factor for chronic venous disease (CVD). Aging is associated with venous valvular deterioration, reduced venous wall elasticity, and increased reflux, all of which contribute to elevated disease risk [ 5 ] . These findings suggest increased clinical vigilance for middle-aged and older populations. BMI also had a significant nonlinear effect, with scores sharply increasing when BMI exceeded 27. This result is supported by studies from Vlajinac et al. [ 6 ] and Joseph et al. [ 7 ] , which also demonstrated a positive association between obesity and CVD severity. Obesity exacerbates disease progression by increasing venous pressure, wall tension, and valvular dysfunction. Therefore, high-BMI patients should receive targeted health education and weight management interventions to delay disease progression [ 5 ] . Regarding gender differences, female patients exhibited a higher overall incidence than males and demonstrated greater VCSS sensitivity at higher BMI levels. The Edinburgh Vein Study noted that multiparity increases the risk of telangiectasia, and hormonal fluctuations may weaken venous wall protection. Additionally, differences in fat distribution may accelerate disease progression [ 8 ] . In clinical practice, high-BMI women with multiple pregnancies should receive particular attention. Family history was reaffirmed as an independent risk factor, consistent with previous literature. The underlying mechanisms may involve inherited abnormalities in venous wall structure and valve function, which increase genetic susceptibility. Socioeconomic similarities within families may also play a role. Individuals with VV are often more aware of familial cases than those without VV [ 9 ] . Early screening and regular monitoring are recommended for high-risk groups with a family history. Hypertension and diabetes significantly increased VCSS scores, likely due to endothelial dysfunction, microcirculatory impairment, and chronic venous hypertension. These conditions promote venous dilation and valvular insufficiency, which in turn cause reflux and microcirculatory hypoxia, inflammation, and fibrosis, ultimately leading to ulceration [ 10 ] . Comprehensive management of these chronic conditions is essential to support VV treatment. Lifestyle factors (smoking, alcohol consumption, and behavioral risks) were strongly associated with VCSS scores, highlighting the importance of lifestyle interventions in venous disease management. Prolonged sitting, standing, and heavy physical labor elevate venous pressure and valve injury risk. Studies abroad have shown that heavy labor not only increases the risk of developing varicose veins but also raises recurrence rates after treatment [ 11 ] . Patient education should emphasize moderate exercise and early compression therapy to prevent venous edema [ 12 ] . Smoking and drinking may harm vascular endothelium by increasing blood viscosity and inflammation, promoting atherosclerosis and microangiopathy, thus exacerbating venous disease. Smoking cessation and alcohol moderation are strongly recommended [ 13 ] . Valvular insufficiency directly impairs venous return and is a well-established pathophysiological basis of venous disease. Valve dysfunction causes retrograde flow and elevated lower limb venous pressure, creating a vicious cycle that accelerates disease progression [ 14 ] . Early detection and management of valvular insufficiency are clinically essential [ 15 ] . Nonetheless, this study has several limitations: it is a single-center cross-sectional analysis, lacking longitudinal follow-up, which limits the generalizability of its conclusions. Recall bias may affect self-reported lifestyle factors. Additionally, potential variables such as height and occupation were not included. Future research should adopt multicenter, prospective designs and incorporate broader variables to validate and expand upon these findings. Conclusion These findings hold significant clinical relevance. As a common condition, lower extremity varicose veins can lead to severe complications such as leg ulcers and deep vein thrombosis. Understanding its risk factors is crucial for prevention and early diagnosis [ 16 ] . This study further clarifies the impact of various risk factors on varicose veins and emphasizes the importance of comprehensive risk profiling. Targeted strategies—including monitoring high-risk individuals, promoting healthy lifestyles, and enhancing chronic disease management—may reduce disease incidence and progression while improving patients’ quality of life. Clinically, these results may aid physicians in recognizing key risk factors, developing individualized prevention and treatment plans, and enhancing patient adherence and treatment efficacy. Declarations Funding This research received no external funding. Acknowledgments The authors thank all staff at the Affiliated Hospital of Xuzhou Medical University who assisted with data collection and patient coordination. We are also grateful to the patients who participated in this study. Competing Interests The authors declare that they have no competing interests. 1. Ethical Approval This study was approved by the [Medical Ethics Committee of the Affiliated Hospital of Xuzhou Medical University] (Approval No.: XYFY2025-KL406-01). The study was conducted in accordance with the Declaration of Helsinki and relevant guidelines and regulations. Clinical trial number: not applicable. 2. Consent to Participate The requirement for informed consent was waived by the Medical Ethics Committee of the Affiliated Hospital of Xuzhou Medical University due to the retrospective nature of the study and the use of anonymized clinical data. 3. Consent to publish All authors consent to publication. Consent for Publication Not applicable. Authors' Contributions YXZ and DTL contributed equally to this work and share first authorship.NW is the corresponding author and the guarantor of this research.QL is listed as the second author, and KZ as the third author, based on their respective contributions. YXZ: Study design, data collection, statistical analysis, and manuscript drafting. DTL: Data analysis, interpretation of results, and manuscript writing. QL: Data management, literature search, and manuscript revision. KZ: Assisted in statistical modeling and figure preparation. NW: Supervised the study, finalized the methodology, and critically reviewed and approved the final manuscript. All authors read and approved the final version of the manuscript. References Mei JC, Zheng YH. Expert consensus on the diagnosis and treatment of primary superficial varicose veins of the lower extremities (2021 version). J Vasc Endovasc Surg (China). 2021;7(7):762–72. 10.19418/j.cnki.issn2096-0646.2021.07.02 . Lim CS, Davies AH. Pathogenesis of primary varicose veins. Br J Surg. 2009;96(11):1231–42. Li L. Key updates of the 2023 SVS/AVF/AVLS clinical practice guidelines for the management of varicose veins of the lower extremities. Chin J Gen Surg. 2023;32(12):1842–53. Mok Y, Ballew HS, Newton KA, et al. Demographic and clinical risk factors of developing clinically-recognized varicose veins in older adults. Am J Prev Med. 2024;68(4):674–81. Lena AK, Eberhard R, Bernd K et al. Differences in risk profile associated with varicose veins and chronic venous insufficiency – results from the Bonn Vein Study 1. VASA. 2024. Vlajinac H, Marinkovic J, Maksimovic M, et al. Body mass index and primary chronic venous disease – a cross-sectional study. Eur J Vasc Endovasc Surg. 2013;45(3):293–8. Chandu V, DKG JPP, et al. Effect of junctional reflux on the venous clinical severity score in patients with insufficiency of the great saphenous vein (JURY study). J Vasc Surg Venous Lymphat Disord. 2023;12(2):101700. YABC SCB. Women benefit from endovenous ablation with fewer complications: analysis of the Vascular Quality Initiative Varicose Vein Registry. J Vasc Surg Venous Lymphat Disord. 2022;10(6):1229–e12372. Chiesa R, Marone E, Limoni C, et al. Demographic factors and their relationship with the presence of CVI signs in Italy: the 24-Cities Cohort Study. Eur J Vasc Endovasc Surg. 2005;30(6):674–80. He N, Zhang TF, Liang ZK, et al. Current status and evaluation of minimally invasive treatment for varicose veins of the lower limbs. Chin J Pract Surg. 2023;43(12):1364–8. 10.19538/j.cjps.issn1005-2208.2023.12.09 . Joseph N, Thouseef BA. A multicenter review of epidemiology and management of varicose veins for national guidance. Ann Med Surg. 2016;8:21–7. Lindsay LSSNK, Marlene R. Graduated compression stockings for the initial treatment of varicose veins in people without venous ulceration. Cochrane Database Syst Rev. 2021;7(7):CD008819. Zhen J. Risk factors and interventions for venous ulcer formation in patients with lower limb varicose veins. Chin Gen Nurs. 2022;20(32):4543–5. Wang QZ, Zhang L, Song FC, et al. Research progress on the sources of venous reflux in lower limb varicose veins. Chin J Vasc Surg. 2023;8(3):311–4. 10.3760/cma.j.cn101411-20220906-00085 . Song XJ, Ye W. Etiology, clinical manifestations and treatment methods of lower extremity varicose veins. J Vasc Endovasc Surg (China). 2020;6(5):460–2. 10.19418/j.cnki.issn2096-0646.2020.05.019 . Alev JME. Clinical features of venous insufficiency and the risk of venous thrombosis in older people. Br J Haematol. 2015;171(3):417–23. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Oct, 2025 Editor assigned by journal 03 Oct, 2025 Reviews received at journal 30 Sep, 2025 Reviews received at journal 27 Sep, 2025 Reviewers agreed at journal 26 Sep, 2025 Reviewers agreed at journal 19 Sep, 2025 Reviewers invited by journal 16 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 15 Sep, 2025 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7318976","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":517432260,"identity":"8f3b2fb0-60b9-47ff-8c35-7f2d16a0c752","order_by":0,"name":"Yuanxuan Zhang","email":"","orcid":"","institution":"The Affiliated Hospital of Xuzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanxuan","middleName":"","lastName":"Zhang","suffix":""},{"id":517432264,"identity":"95364a3b-967b-4517-975b-4f87d705f420","order_by":1,"name":"Duntao Lv","email":"","orcid":"","institution":"The Affiliated Hospital of Xuzhou 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06:55:43","extension":"html","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64392,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/8e025b85a27f2b97f7cefd09.html"},{"id":92233338,"identity":"8fa1faa7-c62e-475a-81e5-35abbf18e61d","added_by":"auto","created_at":"2025-09-26 06:55:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27294,"visible":true,"origin":"","legend":"\u003cp\u003eillustrates that family history, behavioral risk factors, valvular insufficiency, alcohol consumption, hypertension, and diabetes are independent positive predictors of higher VCSS scores. In contrast, male gender is a negative predictor. The magnitude of each factor’s impact is clearly quantified.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/ee38e6959774a9364796234f.jpeg"},{"id":92234414,"identity":"374fb10f-4a7e-42b1-9fe6-780f076829ce","added_by":"auto","created_at":"2025-09-26 07:03:43","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23050,"visible":true,"origin":"","legend":"\u003cp\u003eshows the nonlinear relationship between BMI and VCSS scores. The graph demonstrates a sharp rise in scores when BMI exceeds approximately 27, indicating a clear nonlinear effect.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/ec0b9de94f6c81b04d21b559.jpeg"},{"id":92233347,"identity":"4b667070-224a-4ee0-b174-786dad5c80ea","added_by":"auto","created_at":"2025-09-26 06:55:43","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46320,"visible":true,"origin":"","legend":"\u003cp\u003ereveals a distinct nonlinear relationship between age and VCSS scores. Scores remain stable or slightly decrease before age 40, but increase rapidly after age 50, indicating that the relationship between age and disease risk is not simply a linear accumulation.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/612465d379adc03ade6f3abf.jpeg"},{"id":92233339,"identity":"8a9f2c3d-41b1-452b-89d7-f95b65f2bf99","added_by":"auto","created_at":"2025-09-26 06:55:42","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":23182,"visible":true,"origin":"","legend":"\u003cp\u003edemonstrates that the relationship between BMI and VCSS score follows a nonlinear trend for both sexes, with women showing a steeper score increase when BMI exceeds 27. This indicates an interaction effect between gender and BMI.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/786ee2d9718c1e3fa55bd902.jpeg"},{"id":92234413,"identity":"a3577fd4-dc8a-48e0-9272-9626c9c05806","added_by":"auto","created_at":"2025-09-26 07:03:43","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":53618,"visible":true,"origin":"","legend":"\u003cp\u003ethe plot of predicted scores versus residuals, displays an “S”-shaped pattern of non-random fluctuations.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/94824591a4e9de08b5f01f49.jpeg"},{"id":92234415,"identity":"ab782b12-ceb3-42f5-9773-2807c42c13ca","added_by":"auto","created_at":"2025-09-26 07:03:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":669231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7318976/v1/ba233362-5774-47f0-8f9b-98bbcc6151a0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multivariate Regression Analysis of Risk Factors for Lower Extremity Varicose Veins Based on VCSS Scores","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic venous disease of the lower extremities, including varicose veins, is a common condition with a rising global prevalence. In its early and intermediate stages, superficial varicose veins can adversely affect patients\u0026rsquo; quality of life to varying degrees. In advanced stages, the disease may lead to partial loss of work capacity, consume substantial medical resources, and impose significant physical and psychological burdens on patients \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Early manifestations include limb heaviness and discomfort, tortuous and dilated superficial veins. As the disease progresses, symptoms such as pruritus, skin pigmentation, desquamation, lipodermatosclerosis, and even ulceration, hemorrhage, or thrombophlebitis may occur \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAccurate assessment of disease severity is therefore essential for early intervention and individualized treatment planning. The Venous Clinical Severity Score (VCSS) encompasses ten evaluation items, including venous symptoms, varicosities, venous edema, skin pigmentation, inflammatory changes, induration, number and duration of active ulcers, ulcer size, and use of compression therapy \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. As a standardized tool for assessing clinical severity, the VCSS is instrumental in guiding clinical decision-making.\u003c/p\u003e\u003cp\u003eMultiple international studies have identified age, female sex, taller stature, obesity, pregnancy, and family history as risk factors for varicose veins. However, findings on other factors, such as hypertension, smoking, and obesity-related indices, have been inconsistent \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Notably, most prior studies focused on predominantly White or relatively younger populations. This study utilizes a Generalized Additive Model (GAM) to systematically analyze the risk factors associated with primary lower extremity varicose vein severity in a domestic patient cohort, aiming to clarify the contribution of each factor to disease progression and provide theoretical support for prevention and treatment strategies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e1. Study Population:A total of 751 patients with a confirmed diagnosis of primary lower extremity varicose veins by ultrasound or digital subtraction angiography (DSA) were enrolled at the Affiliated Hospital of Xuzhou Medical University between June 2024 and June 2025. Patient data, including height, weight, smoking and alcohol history, behavioral factors, medical history, and quality of life, were extracted from hospital admission records.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e2. Research Instruments:The severity of varicose veins was assessed using the standardized Venous Clinical Severity Score (VCSS). Demographic characteristics, medical history, and lifestyle factors were also recorded.\u003c/p\u003e\n \u003cp\u003e3. Statistical Analysis:Data were analyzed using R software. A Generalized Additive Model (GAM) was employed to identify significant risk factors. Results were presented in the form of a forest plot, along with confidence intervals and P-values.\u003c/p\u003e\n \u003cp\u003e4. Inclusion Criteria:Patients who completed relevant examinations and were diagnosed with primary lower extremity varicose veins via ultrasound or DSA imaging after admission, with complete and reliable clini\u003c/p\u003e\n \u003cp\u003ecal data.Exclusion Criteria:Patients with secondary varicose veins due to other causes, such as Budd-Chiari syndrome or iliac vein compression syndrome; patients who had received any form of surgical or medical treatment prior to admission; or patients with incomplete or inaccurate data.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTo explore the associations between clinical variables and VCSS scores, a Generalized Additive Model (GAM) was employed to account for potential nonlinear effects of age and BMI. The model demonstrated a good fit, with an adjusted R\u0026sup2; of 0.820 and an explained deviance of 82.5%.\u003c/p\u003e\n\u003cp\u003eThe analysis revealed significant nonlinear relationships between both age and BMI with VCSS scores. Specifically, the smooth term for age had an estimated degrees of freedom (edf) of 7.31 (F\u0026thinsp;=\u0026thinsp;5.94, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating a flexible, nonlinear association with the score. BMI also exhibited a significant nonlinear effect (edf\u0026thinsp;=\u0026thinsp;4.13, F\u0026thinsp;=\u0026thinsp;20.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eRegarding linear parameters, male patients had slightly lower scores than females (\u0026beta; = -0.411, standard error\u0026thinsp;=\u0026thinsp;0.131, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Several binary clinical factors were significantly associated with increased VCSS scores, including family history (\u0026beta;\u0026thinsp;=\u0026thinsp;3.13, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), hypertension (\u0026beta;\u0026thinsp;=\u0026thinsp;1.45, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), diabetes (\u0026beta;\u0026thinsp;=\u0026thinsp;1.20, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), smoking (\u0026beta;\u0026thinsp;=\u0026thinsp;1.14, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), alcohol consumption (\u0026beta;\u0026thinsp;=\u0026thinsp;1.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), behavioral risk factors (\u0026beta;\u0026thinsp;=\u0026thinsp;2.02, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and valvular insufficiency (\u0026beta;\u0026thinsp;=\u0026thinsp;1.50, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1 . These results show that all listed factors were significantly associated with higher VCSS scores, with family history and behavioral risk factors showing the strongest effects.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003esummarizes the associations between each factor and the VCSS score as determined by the GAM model.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard Error\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003et Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-3.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily history\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.453\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBehavioral risk factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eValvular insufficiency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;2 . This table indicates that both age and BMI exhibit significant nonlinear associations with VCSS scores in the GAM model.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAnalysis of Nonlinear Effects of Age and BMI in the GAM Model .\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNonlinear Variable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEstimated Degrees of Freedom (edf)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eReference Degrees of Freedom (Ref.df)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF Value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFamily history suggests a genetic predisposition, while behavioral risk factors show a strong influence on VCSS scores. Valvular insufficiency directly affects hemodynamics. Gender differences may be attributed to the protective role of estrogen and variations in lipid metabolism. In clinical evaluation and intervention, particular attention should be paid to patients with a positive family history, unhealthy lifestyles, and valvular dysfunction. Additionally, differences in score sensitivity by gender should be considered.\u003c/p\u003e\n\u003cp\u003eThis finding aligns with previous international studies and suggests that obesity induces chronic inflammation, insulin resistance, and lipid metabolism disorders, which collectively accelerate the progression of chronic diseases, as reflected in the sharp increase in VCSS scores. Patients with a BMI over 27 should be classified as high-risk and targeted for intensified intervention. BMI control strategies should focus on preventing surpassing this risk threshold.\u003c/p\u003e\n\u003cp\u003eThis pattern may be due to a combination of factors in older adults, such as atherosclerosis, endothelial dysfunction, and immunosenescence, contributing to a significant rise in scores. In contrast, compensatory mechanisms may still be active in middle-aged individuals, resulting in more stable score changes. Risk assessment should not rely solely on age groupings but should account for the sharp increase in risk among the elderly, supporting early intervention strategies.\u003c/p\u003e\n\u003cp\u003eThis phenomenon may be explained by the higher likelihood of visceral fat accumulation, chronic inflammation, and hormonal dysregulation in obese women. These factors may synergistically drive a rapid rise in VCSS scores. In clinical risk assessments and interventions, special attention should be paid to women with high BMI, as their scores are more sensitive to BMI increases. Gender-specific intervention strategies are recommended.\u003c/p\u003e\n\u003cp\u003eThis statistical pattern suggests possible threshold effects in the influence of BMI and age on disease progression\u0026mdash;risks may increase markedly or plateau beyond certain thresholds. Thus, linear models may not fully capture these pathophysiological dynamics and may fail to accurately predict risk scores, especially for patients at very high or very low risk. In clinical practice, pure linear models should be used cautiously, and more flexible statistical models\u0026mdash;such as GAM\u0026mdash;are recommended for risk assessment.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, all identified factors significantly influenced VCSS scores. The following interpretations are based on these findings:\u003c/p\u003e\u003cp\u003eAge showed a nonlinear relationship with VCSS scores, with scores rising rapidly after age 50, indicating a higher risk in older patients. This is consistent with findings from the Bonn Vein Study, which identified age as an independent risk factor for chronic venous disease (CVD). Aging is associated with venous valvular deterioration, reduced venous wall elasticity, and increased reflux, all of which contribute to elevated disease risk\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. These findings suggest increased clinical vigilance for middle-aged and older populations.\u003c/p\u003e\u003cp\u003eBMI also had a significant nonlinear effect, with scores sharply increasing when BMI exceeded 27. This result is supported by studies from Vlajinac et al.\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e and Joseph et al.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, which also demonstrated a positive association between obesity and CVD severity. Obesity exacerbates disease progression by increasing venous pressure, wall tension, and valvular dysfunction. Therefore, high-BMI patients should receive targeted health education and weight management interventions to delay disease progression\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRegarding gender differences, female patients exhibited a higher overall incidence than males and demonstrated greater VCSS sensitivity at higher BMI levels. The Edinburgh Vein Study noted that multiparity increases the risk of telangiectasia, and hormonal fluctuations may weaken venous wall protection. Additionally, differences in fat distribution may accelerate disease progression\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In clinical practice, high-BMI women with multiple pregnancies should receive particular attention.\u003c/p\u003e\u003cp\u003eFamily history was reaffirmed as an independent risk factor, consistent with previous literature. The underlying mechanisms may involve inherited abnormalities in venous wall structure and valve function, which increase genetic susceptibility. Socioeconomic similarities within families may also play a role. Individuals with VV are often more aware of familial cases than those without VV\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Early screening and regular monitoring are recommended for high-risk groups with a family history.\u003c/p\u003e\u003cp\u003eHypertension and diabetes significantly increased VCSS scores, likely due to endothelial dysfunction, microcirculatory impairment, and chronic venous hypertension. These conditions promote venous dilation and valvular insufficiency, which in turn cause reflux and microcirculatory hypoxia, inflammation, and fibrosis, ultimately leading to ulceration\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Comprehensive management of these chronic conditions is essential to support VV treatment.\u003c/p\u003e\u003cp\u003eLifestyle factors (smoking, alcohol consumption, and behavioral risks) were strongly associated with VCSS scores, highlighting the importance of lifestyle interventions in venous disease management. Prolonged sitting, standing, and heavy physical labor elevate venous pressure and valve injury risk. Studies abroad have shown that heavy labor not only increases the risk of developing varicose veins but also raises recurrence rates after treatment\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Patient education should emphasize moderate exercise and early compression therapy to prevent venous edema\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSmoking and drinking may harm vascular endothelium by increasing blood viscosity and inflammation, promoting atherosclerosis and microangiopathy, thus exacerbating venous disease. Smoking cessation and alcohol moderation are strongly recommended\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eValvular insufficiency directly impairs venous return and is a well-established pathophysiological basis of venous disease. Valve dysfunction causes retrograde flow and elevated lower limb venous pressure, creating a vicious cycle that accelerates disease progression\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Early detection and management of valvular insufficiency are clinically essential\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNonetheless, this study has several limitations: it is a single-center cross-sectional analysis, lacking longitudinal follow-up, which limits the generalizability of its conclusions. Recall bias may affect self-reported lifestyle factors. Additionally, potential variables such as height and occupation were not included. Future research should adopt multicenter, prospective designs and incorporate broader variables to validate and expand upon these findings.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThese findings hold significant clinical relevance. As a common condition, lower extremity varicose veins can lead to severe complications such as leg ulcers and deep vein thrombosis. Understanding its risk factors is crucial for prevention and early diagnosis \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. This study further clarifies the impact of various risk factors on varicose veins and emphasizes the importance of comprehensive risk profiling. Targeted strategies\u0026mdash;including monitoring high-risk individuals, promoting healthy lifestyles, and enhancing chronic disease management\u0026mdash;may reduce disease incidence and progression while improving patients\u0026rsquo; quality of life. Clinically, these results may aid physicians in recognizing key risk factors, developing individualized prevention and treatment plans, and enhancing patient adherence and treatment efficacy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all staff at the Affiliated Hospital of Xuzhou Medical University who assisted with data collection and patient coordination. We are also grateful to the patients who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003eThis study was approved by the [Medical Ethics Committee of the Affiliated Hospital of Xuzhou Medical University] (Approval No.: XYFY2025-KL406-01). The study was conducted in accordance with the Declaration of Helsinki and relevant guidelines and regulations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003eThe requirement for informed consent was waived by the Medical Ethics Committee of the Affiliated Hospital of Xuzhou Medical University due to the retrospective nature of the study and the use of anonymized clinical data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Consent to publish\u0026nbsp;\u003c/strong\u003eAll authors consent to publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYXZ and DTL contributed equally to this work and share first authorship.NW is the corresponding author and the guarantor of this research.QL is listed as the second author, and KZ as the third author, based on their respective contributions.\u003c/p\u003e\n\u003cp\u003eYXZ: Study design, data collection, statistical analysis, and manuscript drafting.\u003c/p\u003e\n\u003cp\u003eDTL: Data analysis, interpretation of results, and manuscript writing.\u003c/p\u003e\n\u003cp\u003eQL: Data management, literature search, and manuscript revision.\u003c/p\u003e\n\u003cp\u003eKZ: Assisted in statistical modeling and figure preparation.\u003c/p\u003e\n\u003cp\u003eNW: Supervised the study, finalized the methodology, and critically reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMei JC, Zheng YH. Expert consensus on the diagnosis and treatment of primary superficial varicose veins of the lower extremities (2021 version). J Vasc Endovasc Surg (China). 2021;7(7):762\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19418/j.cnki.issn2096-0646.2021.07.02\u003c/span\u003e\u003cspan address=\"10.19418/j.cnki.issn2096-0646.2021.07.02\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLim CS, Davies AH. Pathogenesis of primary varicose veins. Br J Surg. 2009;96(11):1231\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi L. Key updates of the 2023 SVS/AVF/AVLS clinical practice guidelines for the management of varicose veins of the lower extremities. Chin J Gen Surg. 2023;32(12):1842\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMok Y, Ballew HS, Newton KA, et al. 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J Vasc Endovasc Surg (China). 2020;6(5):460\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19418/j.cnki.issn2096-0646.2020.05.019\u003c/span\u003e\u003cspan address=\"10.19418/j.cnki.issn2096-0646.2020.05.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlev JME. Clinical features of venous insufficiency and the risk of venous thrombosis in older people. Br J Haematol. 2015;171(3):417\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Medicine](https://link.springer.com/journal/44337)","snPcode":"44337","submissionUrl":"https://submission.springernature.com/new-submission/44337/3","title":"Discover Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Varicose veins, Risk factors, Venous Clinical Severity Score, Epidemiology","lastPublishedDoi":"10.21203/rs.3.rs-7318976/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7318976/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aimed to compare the characteristics of risk factors for lower limb varicose veins (VV) and identify key variables associated with disease severity to guide clinical prevention and management strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA cross-sectional study was conducted on 751 patients with primary lower limb varicose veins admitted to the Affiliated Hospital of Xuzhou Medical University between June 2024 and June 2025. Clinical data were collected, and disease severity was assessed using the Venous Clinical Severity Score (VCSS). A Generalized Additive Model (GAM) was applied to analyze the association between VCSS scores and various risk factors, including age, gender, BMI, family history, hypertension, diabetes, smoking, alcohol consumption, behavioral factors, and venous valve dysfunction. Residual analysis was performed to assess model fit.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAge, gender, BMI, family history, hypertension, diabetes, smoking, alcohol use, behavioral factors, and valve dysfunction were all significantly associated with VCSS scores (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Female patients showed a slightly higher prevalence than males. Patients who smoked (β\u0026thinsp;=\u0026thinsp;1.14) or consumed alcohol (β\u0026thinsp;=\u0026thinsp;1.47) had higher VCSS scores. Obesity was also a major aggravating factor. Chronic diseases such as hypertension (β\u0026thinsp;=\u0026thinsp;1.45) and diabetes (β\u0026thinsp;=\u0026thinsp;1.20) increased the disease burden. Valve dysfunction (β\u0026thinsp;=\u0026thinsp;1.50) had a considerable impact on VCSS scores. The strongest associations were observed for family history (β\u0026thinsp;=\u0026thinsp;3.13) and behavioral factors (β\u0026thinsp;=\u0026thinsp;2.04), highlighting the importance of early behavioral intervention and genetic risk management.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe severity of primary lower limb varicose veins is influenced by a range of risk factors. Clinical management strategies should take these into account, with targeted interventions. For instance, patients with behavioral risk factors may benefit from early use of compression stockings to prevent venous edema, while those with high BMI or a history of smoking should be advised to adopt weight reduction and smoking cessation programs promptly.\u003c/p\u003e","manuscriptTitle":"Multivariate Regression Analysis of Risk Factors for Lower Extremity Varicose Veins Based on VCSS Scores","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-26 06:55:37","doi":"10.21203/rs.3.rs-7318976/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-03T08:22:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-03T08:21:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-30T08:53:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-27T08:11:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272007923045026226926444823236823343482","date":"2025-09-26T06:56:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247052399221302930158612962994791781342","date":"2025-09-19T05:54:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-16T11:39:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T10:25:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Medicine","date":"2025-09-15T10:07:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Medicine](https://link.springer.com/journal/44337)","snPcode":"44337","submissionUrl":"https://submission.springernature.com/new-submission/44337/3","title":"Discover Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d3a9418a-9621-456e-a235-8735c3c472b1","owner":[],"postedDate":"September 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-10-23T12:53:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-26 06:55:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7318976","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7318976","identity":"rs-7318976","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}