The relationship between high intensity activities and kidney stone: A cross-sectional survey of NHANES

The relationship between high intensity activities and kidney stone: A cross-sectional survey of NHANES | 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 The relationship between high intensity activities and kidney stone: A cross-sectional survey of NHANES Fengwei Nong, Zhengfang Liang, Runmin Chen, Yongping Huang, Jie Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5305949/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Kidney stone disease (KSD) occurs in a wide range of ages and is influenced by multiple factors. Early detection and elimination of risk factors for KSD can effectively reduce the incidence of KSD. Methods In this research, we included KSD participants from the National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2015. Baseline characteristics of the participants were investigated using Student's t-tests and chi-square tests. Subsequently, the relationship between high intensity activities (HIA) and KSD was investigated through multifactor glm regression modeling. In addition, the linear relationship between them was explored by smoothing curves. Finally, the predictive performance of HIA on KSD was explored based on receiver operating characteristic (ROC) curves. Results At first, 6,642 subjects were finally recruited for this study. The baseline statistical table showed that the exposure factor (time spent in HIA) was chosen to have a significant differentiation for KSD. In addition, HIA was significantly associated with KSD in all three models, with OR greater than 1 and P < 0.05. The smoothed curves showed that short periods of HIA did not increase the risk of KSD, but over a certain period of time greatly increased the risk of KSD. Stratified analysis results showed that exposure factors and race, educational status, and gout were significantly associated with KSD in Model 3. Eventually, ROC curve indicated the prediction for HIA to KSD was relatively accurate. Conclusion This study revealed a link between HIA and KSD, with HIA over a certain period of time greatly increasing the risk of KSD. kidney stone disease high intensity activities NHANES association Figures Figure 1 Figure 2 Figure 3 1. Introduction Kidney Stone Disease (KSD), a prevalent urinary tract condition, is characterized by the development of crystals within the kidneys, which can lead to various clinical symptoms such as pain, hematuria, vomiting, and even renal failure, affecting more than 10% of the world's population [1, 2] . The pathogenesis of KSD is intricate, intricately intertwined with dietary habits, environmental factors, and metabolic states [3, 4] . Fortunately, the therapeutic landscape for KSD is well-established, encompassing conservative management, extracorporeal shockwave lithotripsy (ESWL), and surgical interventions. However, despite successful stone removal, the 5-year recurrence rate remains as high as 50% [5, 6] . Therefore, early identification and elimination of risk factors for KSD is the key to reducing the incidence and recurrence rate. High intensity activities (HIA) usually refers to physical activity or exercise training that requires the body to perform high energy output and intense effort over a short period of time. This type of activity can significantly increase heart rate, respiratory rate and metabolic rate, which effectively promotes cardiorespiratory function and overall physical fitness [7, 8] . HIA has been widely used in competitive sports, physical training, rehabilitation and daily fitness [9, 10] . In recent years, significant progress has been made in the study of the relationship between HIA and cardiovascular health, metabolic syndrome, and diabetes. Multiple studies have shown that regular HIA helps to enhance cardiorespiratory function, improve blood glucose control, and reduce the risk of chronic diseases [11, 12] . Studies have shown that within a certain range, the prevalence of kidney stones decreases with the increase of exercise intensity [13] . However, other studies have shown that low-intensity exercise may reduce KSD, while high-intensity exercise may increase KSD, which may be related to the influence of high-intensity exercise on the metabolic environment in the body [14] . The mechanism of HIA's influence on KSD is still unclear, and its potential role needs further study. The purpose of this study was to investigate the association between high-intensity exercise and KSD by using data from the National Health and Nutrition Examination Survey (NHANES) database, so as to provide a new reference for clinical prevention and early intervention of KSD. 2. Materials and Methods 2.1 Study population NHANES ( https://www.cdc.gov/nchs/nhanes/index.htm ) was an annual study of the health of the population of the United States, and all its data were directly accessible. Written informed consent was obtained from all participants. Inclusion criteria were all subjects from 2007 to 2015, and exclusion criteria included (1) missing data on KSD and (2) missing data on variables. A final total of 6,642 subjects were recruited (Table 1 ). Table 1 Preliminary screening of variables Variable Excluding condition Number Gender Missing value 50588 Age Missing value 50588 Race Missing value 50588 Education Refused to answer & Missing value 48823 Economic Missing value 44764 smoke Refused to answer & Missing value 11591 alcohol Don't know & missing value 10314 BMI Missing value 6727 hbp Don't know & missing value 6720 diabetes Don't know & missing value 6714 gout Don't know & missing value 6658 outcome Don't know & missing value 6642 2.2 Definition of variables KSD was measured by asking ‘Have you ever had KSD?’ Participants who answered ‘yes’ were considered to have KSD (KIQ026) as an outcome. Age (DMDHRAGE) was a continuous variable; gender (RIAGENDR) was divided into male and female; race (RIDRETH1) was classified into four groups: non-Hispanic white, non-Hispanic black, Mexican American, and other; and educational status (DMDHREDU) was subdivided into three groups: high school, above high school, and below high school; economic status (INDFMPIR) was categorized into 3 groups based on Poverty Income Ratio (PIR): lowest ( 3.5-5); smoking status (SEQN) was subclassified into smokers (at least 100 cigarettes in a lifetime) and non-smokers (less than 100 cigarettes in a lifetime); and alcohol consumption (ALQ100/ALQ101) was categorized as the ability to have 12 drinks in a year; Body Mass Index (BMI, BMXBMI) computed as weight/height squared (kg/m 2 ), sorted into < 20, 20–25, 25–30 and 30 kg/m 2 or more; presence of high blood pressure (BPQ020), diabetes (DIQ010), gout (MCQ160n\MCQ160N) (Table 2 ). Table 2 Definition of variable ID Definition Category Year KIQ026 Have you ever had kidney stones? que 2007–2020 DMDHRAGE age demo 1999–2016 RIDRETH1 race demo 1999–2020 RIAGENDR sex demo 1999–2020 DMDHREDU Educational level demo 1999–2016 INDFMPIR Economic situation demo 1999–2020 SEQN smoking que 1999–2020 ALQ100\ALQ101 Drinking: 12 drinks a year que 1999–2000 BMXBMI bmi exam 1999–2020 BPQ020 hypertension que 1999–2020 DIQ010 diabetes que 1999–2020 MCQ160n\ MCQ160N ventilate que 2007–2018 2.3 Risk correlation analysis To understand the association between exposure factors and the risk of KSD, 2 adjusted models were constructed in which all covariates were assumed to interact with disease. 3 sequential multifactor glm regression models were constructed using the nhanesA package version 1.0.2 ( https://cran.r-project.org/package=nhanesA ). Model 1: exposure factor-high intensity activity (PAD615). Model 2: adjusted for age, race, gender. Model 3: further adjusted for educational status, economic status, smoking status, drinking status, BMI, hypertension, diabetes, gout (MCQ160n\MCQ160N). 2.4 Statistical analysis For between-group comparisons and description of baseline characteristics, we used two-sample t-test or Wilcoxon test for variables that were continuous, and chi-square test or Fisher exact test for categorical variables. Three logistic regression models were utilized to evaluate relationship between exposure factors (high intensity activity) and KSD, and adjusted odds ratio (OR) values and 95% confidence intervals were counted. Stratified analyses of age, gender, and BMI were conducted to further explore the correlation between exposure factors and the risk of KSD. Finally, after adjusting for covariates, the subjects' work characteristics (ROC) curves were analyzed with pROC package version 1.18.0 [15] . Statistical analyses were carried out with R language. All tests were two-tailed with P < 0.05. 3. Results 3.1 Baseline characteristics Data from various clinical information on the number of people included were analyzed by t-test or chi-square test to determine if they were correlated with KSD, and the baseline statistical table showed that the exposure factor PAD615 (time spent in HIA) was chosen to have a significant differentiation of KSD (Table 3 ). Table 3 Baseline statistical tables level 0 1 p n 1061 125 age (mean (SD)) 46.77 (15.36) 50.30 (13.56) 0.014 race (%) Mexican American 137 (12.9) 18 (14.4) < 0.001 Non-Hispanic Black 230 (21.7) 4 ( 3.2) Non-Hispanic White 543 (51.2) 83 (66.4) Other Hispanic 80 ( 7.5) 11 ( 8.8) Other Race - Including Multi-Racial 71 ( 6.7) 9 ( 7.2) gender (%) Female 302 (28.5) 44 (35.2) 0.143 Male 759 (71.5) 81 (64.8) edu (%) 9-11th Grade (Includes 12th grade with no diploma) 180 (17.0) 30 (24.0) 0.089 College Graduate or above 120 (11.3) 16 (12.8) High School Grad/GED or equivalent 91 ( 8.6) 8 ( 6.4) High School Grad/GED or Equivalent 220 (20.7) 29 (23.2) Less Than 9th Grade 101 ( 9.5) 4 ( 3.2) Some College or AA degree 349 (32.9) 38 (30.4) Economic (mean (SD)) 2.13 (1.53) 2.23 (1.46) 0.499 smoke (%) Every day 491 (46.3) 57 (45.6) 0.18 Not at all 449 (42.3) 60 (48.0) Some days 121 (11.4) 8 ( 6.4) alcohol (%) No 105 ( 9.9) 16 (12.8) 0.391 Yes 956 (90.1) 109 (87.2) gout (%) No 1017 (95.9) 116 (92.8) 0.182 Yes 44 ( 4.1) 9 ( 7.2) diabetes (%) Borderline 18 ( 1.7) 5 ( 4.0) 0.001 No 952 (89.7) 98 (78.4) Yes 91 ( 8.6) 22 (17.6) hbp (%) No 703 (66.3) 67 (53.6) 0.007 Yes 358 (33.7) 58 (46.4) BMI (%) 30 589 (55.5) 85 (68.0) 20_30 399 (37.6) 34 (27.2) PAD615 (mean (SD)) 188.78 (154.57) 221.64 (164.83) 0.026 3.2 Association of HIA with KSD The association analysis between exposure factor and outcome showed that HIA was significantly associated with KSD in all three models, with OR greater than 1 and P < 0.05 (Table 4 ). The smoothed curves showed that short periods of HIA did not increase the risk of KSD, but over a certain period of time greatly increased the risk of KSD (Fig. 1 ). Stratified analyses of patients were performed by combining Model 3 to further confirm stability of correlation between exposure factors and KSD risk in various populations. The results showed that exposure factors and race, educational status, and gout were significantly associated with KSD in Model 3 (Fig. 2 ). Table 4 Correlation analysis of exposure factors and outcomes exposure model1_OR(95%_CI) model2_OR(95%_CI) model3_OR(95%_CI) PAD615 1.001e + 00( 1e + 00-1.003e + 00) 1.002e + 00(1.001e + 00-1.004e + 00) 1.002e + 00(1.001e + 00-1.004e + 00) p_value 1.63E-02 3.99E-03 2.41E-03 3.3 HIA offered a favorable prediction of KSD The ROC curve indicated that area under the curve (AUC) of model 3 for the prediction of the risk of KSD was > 0.7, suggesting that the prediction was relatively accurate (Fig. 3 ). It also revealed that the exposure factor could be a good predictor of the risk of the disease under the influence of various factors. 4. Discussion This cross-sectional study comprehensively investigated the association between HIA and KSD. Our research results show that PAD615 (HIA) is associated with the incidence of KSD (Table 3 ). After adjusting for age, race, gender and other aspects in further risk association analysis, HIA still shows a significant relationship with KSD, and short-term HIA does not increase the risk of KSD. However, over a certain period of time, the risk of KSD is greatly increased (Fig. 1 ). Over the past 30 years, the incidence of KSD has nearly tripled in relative terms and increased by 5.6 percent in absolute terms. The increase in the prevalence of KSD was significant across all ages, genders, and ethnicities [16] . At present, the renal end treatment mainly includes conservative treatment, extracorporeal shock wave lithotomy and surgical treatment, and the recurrence rate of KSD is very high, which brings heavy economic burden to patients and society, and the annual healthcare expenditure of KSD in the United States exceeds 2 billion US dollars [17–19] . In addition, KSD can also cause complications such as urinary tract infection, renal dysfunction, and even life-threatening sepsis, posing a serious threat to human health [8, 20] . At present, it has been established that dehydration and reduced urine volume are the most common risk factors for KSD [21, 22] . Increasing fluid intake and urine volume are important means to prevent stones [23, 24] . Notably, HIA inevitably leads to a sharp decrease in body moisture and dehydration, which may be an important reason for HIA as a risk factor for KSD. In addition to overt water loss, HIA also has a significant impact on metabolism in the body. HIA is bound to result in lactic acid accumulation. As an acidic substance, excessive accumulation of lactic acid in the body will decrease the pH value of the blood, which may lead to metabolic acidosis in severe cases [25] . In order to maintain the acid-base balance in the body, the kidneys remove more acidic substances, resulting in acidic urine. This change in pH can affect the solubility of certain minerals in the urine, thereby increasing the risk of stone formation [26] . In addition, in order to eliminate excessive hydrogen ions, the kidney will reduce the reabsorption of calcium and increase the excretion of calcium in the urine, and the increase of calcium content in the urine is another important reason for the formation of kidney stones [27, 28] . Therefore, HIA may promote the formation of KSD by affecting water and electrolyte balance and acid-base balance. A study on the acute effects of HIA on renal function shows that HIA can cause increased serum creatinine (SCr), indicating that HIA can cause transient subclinical dysfunction of renal function to a certain extent [29] . Animal experiments have shown that HIA can increase the accumulation of serum creatinine and glycogen in mouse kidneys, activate PI3K/AKT/mTOR signaling pathway, induce kidney injury and fibrosis, and kidney injury can also lead to increased risk of kidney stones [30] . Other studies have shown that HIA can lead to the early significant increase of creatine kinase(CK), myoglobin, SCr, microalbuminuria and urine biomarkers indicating renal tubule injury, suggesting the occurrence of kidney injury [31] , and kidney injury and dysfunction promote the nucleation, aggregation and retention of urine crystals in the kidney. It may also produce ineffective crystallization modulators and local supersaturated areas of the mesenchyma, thereby affecting crystallization in the urine and promoting the development of kidney stones [32] . Therefore, it is speculated that HIA may promote the development of KSD by causing kidney injury or renal dysfunction. Other studies have found that HIA is associated with oxidative stress, depending on the pattern, intensity, and duration of exercise, excessive HIA can lead to increased oxidative stress [33] . Structured high-intensity interval training (HIIT) generally improves overall and skeletal muscle metabolic health in different populations, however, if the accumulation of fatigue is not solved, it will cause oxidative stress disorder, and eventually lead to endocrine disorders, immune disorders, systemic inflammation and other adverse consequences [34] . Previous studies have shown that renal crystal deposition is related to the production of reactive oxygen species (ROS) and the activation of inflammasome, and urine supersaturation promotes plaque formation and calcium stone formation in kidney Randall by inducing ROS production and oxidative stress [35] . Oxidative stress can increase the risk of stone formation, and the inflammatory response generated during the formation of kidney stones further aggravates oxidative stress and forms a harmful cycle [36] . A study showed that the level of malondialdehyde (MDA), a marker of oxidative stress in KSD, was positively correlated with the level of oxalate in red blood cells and negatively correlated with the activity of antioxidant protein in red blood cells, indicating that oxidative stress of red blood cells may lead to renal tubule damage and stone accumulation in patients [37] . In animal experiments, it was also found that oxidative stress injury was related to the formation of kidney stones, and a high-sodium diet in mice would cause oxidative stress injury and loss of anti-crystallization defense, thus causing a large number of crystals formation in the kidney [38] . Therefore, excessive HIA may lead to the development of KSD through kidney injury and oxidative stress. Our research has several advantages. We first provide evidence of a relationship between HIA and KSD in a large, cross-sectional, and well-developed dataset. In addition, we performed multivariate logistic analyses and sensitivity analyses adjusted for potential confounders to provide robust associations. This study provides evidence that HIA is a risk factor for KSD and needs attention. Nevertheless, some limitations should be considered. First, the cross-sectional design of NHANES suggests that no causal relationship can be established. Second, interview forums used for data collection can lead to potential bias. Third, some asymptomatic KSD patients are not physically examined and are missed in the database. Finally, there are unobserved confounding factors that may be missed. In conclusion, this study points out that HIA can be used as a predictor of KSD occurrence, providing ideas and strategies for early detection and elimination of risk factors for KSD. Declarations Funding This research was supported by the grant from the project of Young and middle-aged backbone of The Affiliated Hospital of Youjiang Medical University for Nationalities (#Y20212613) and the Basic ability improvement project for young and middle-aged teachers of the Guangxi Zhuang Autonomous Region（#2023KY0551）. Author information Fengwei Nong and Zhengfang Liang contributed equally to this work. Authors and Affiliations Jinan University, Guangzhou, Guangdong Province, China Department of Renal Diseases, Affiliated Hospital of Youjiang Medical University for Nationalites, Baise, Guangxi, China Fengwei Nong&Jie Wang Department of Urinary Surgery, Affiliated Hospital of Youjiang Medical University for Nationalites, Baise, Guangxi, China Key Laboratory of Clinical Diagnosis and Treatment Research of High Incidence Diseases in Guangxi, China Zhengfang Liang, Runmin Chen&Yongping Huang Contributions Jie Wang and Yongping Huang conceived the study, Fengwei Nong and Zhengfang Liang collected and analyzed the data and draw the manuscript, Runmin Chen assisted in extracting and analyzing the data. All authors have read and approved the final manuscript. Corresponding author Correspondence to Jie Wang or Yongping Huang Ethics declarations The NHANES was approved by the NCHS Research Ethics Review Board. 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Nutrition, 2015; 31(7–8): 916–922. Magherini F, Fiaschi T, Marzocchini R, Mannelli M, Gamberi T, Modesti PA, Modesti A. Oxidative stress in exercise training: the involvement of inflammation and peripheral signals[J]. Free Radic Res, 2019; 53(11–12): 1155–1165. Khan SR, Canales BK, Dominguez-Gutierrez PR. Randall's plaque and calcium oxalate stone formation: role for immunity and inflammation[J]. Nat Rev Nephrol, 2021; 17(6): 417–433. Sun Y, Sun H, Zhang Z, Tan F, Qu Y, Lei X, Xu Q, Wang J, Shu L, Xiao H, Yang Z, Liu H. New insight into oxidative stress and inflammatory responses to kidney stones: Potential therapeutic strategies with natural active ingredients[J]. Biomed Pharmacother, 2024; 179: 117333. Ma MC, Chen YS, Huang HS. Erythrocyte oxidative stress in patients with calcium oxalate stones correlates with stone size and renal tubular damage[J]. Urology, 2014; 83(2): 510.e9-17. Huang HS, Ma MC. High Sodium-Induced Oxidative Stress and Poor Anticrystallization Defense Aggravate Calcium Oxalate Crystal Formation in Rat Hyperoxaluric Kidneys[J]. PLoS One, 2015; 10(8): e0134764. 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-5305949","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369523671,"identity":"83910112-0683-46d1-8a36-d490127397c8","order_by":0,"name":"Fengwei Nong","email":"","orcid":"","institution":"1Jinan University","correspondingAuthor":false,"prefix":"","firstName":"Fengwei","middleName":"","lastName":"Nong","suffix":""},{"id":369523673,"identity":"341f98d9-79b7-4899-9c4c-817f1150a276","order_by":1,"name":"Zhengfang Liang","email":"","orcid":"","institution":"3Department of Urinary Surgery, Affiliated Hospital of Youjiang Medical University for Nationalites","correspondingAuthor":false,"prefix":"","firstName":"Zhengfang","middleName":"","lastName":"Liang","suffix":""},{"id":369523676,"identity":"d4561a79-5d6a-4f52-b758-2461e3c13cdc","order_by":2,"name":"Runmin Chen","email":"","orcid":"","institution":"3Department of Urinary Surgery, Affiliated Hospital of Youjiang Medical University for Nationalites","correspondingAuthor":false,"prefix":"","firstName":"Runmin","middleName":"","lastName":"Chen","suffix":""},{"id":369523678,"identity":"bf452c8e-8284-4741-b826-4ad91643f73b","order_by":3,"name":"Yongping Huang","email":"","orcid":"","institution":"3Department of Urinary Surgery, Affiliated Hospital of Youjiang Medical University for Nationalites","correspondingAuthor":false,"prefix":"","firstName":"Yongping","middleName":"","lastName":"Huang","suffix":""},{"id":369523680,"identity":"4079c5cc-8e63-4dc4-b4db-491aee94af4a","order_by":4,"name":"Jie Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACxmYogx8m0EC0FskGYrXAgcEBYrUwtzMfYOapuWO3+UZ2mnQBg43shgPMzx7gdxhbAjPPsWfJ227kbpOewZBmvOEAm7kBfi08Bsw5bIeTzUBaeBgOJ244wMMmgV8L/wfmnH+Hk41ngLX8J0YLDwNzbtthOwMJsJYDxGhhMzj8t+9wgsSZt5uteQySjWceZjPDq8Ww//DDhzO+Hbbnb8/deJunwk6273jzM/xaGhgYDgDpxAaBBCAFCipmfOqBQB5K2zPwHyCgdBSMglEwCkYsAAD9qUeCNJIZWAAAAABJRU5ErkJggg==","orcid":"","institution":"1Jinan University","correspondingAuthor":true,"prefix":"","firstName":"Jie","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-10-21 16:11:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5305949/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5305949/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68884619,"identity":"58c0e344-b269-4264-8d0b-44a1f3f96e00","added_by":"auto","created_at":"2024-11-13 06:27:21","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52783,"visible":true,"origin":"","legend":"\u003cp\u003eSmooth curve fitting model\u003c/p\u003e","description":"","filename":"2.Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5305949/v1/13e0a0edc04313da647fa42e.jpg"},{"id":68884620,"identity":"1003c494-beb6-47f4-a243-a9b41c587267","added_by":"auto","created_at":"2024-11-13 06:27:21","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":169500,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots between variables and diseases\u003c/p\u003e","description":"","filename":"2.Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5305949/v1/77156b736aaad5f3cab109cc.jpg"},{"id":68884618,"identity":"dbebef66-82bd-41db-94aa-42c476736697","added_by":"auto","created_at":"2024-11-13 06:27:21","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":64321,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of Model 3\u003c/p\u003e","description":"","filename":"2.Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5305949/v1/d2c0ff882cd17e4d6a03327d.jpg"},{"id":75609209,"identity":"9d16b5ac-b3aa-4c67-9a54-75d8690a4938","added_by":"auto","created_at":"2025-02-06 09:54:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1004284,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5305949/v1/8488c07a-8ea5-48e2-b2ae-e760c06cf95a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The relationship between high intensity activities and kidney stone: A cross-sectional survey of NHANES","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eKidney Stone Disease (KSD), a prevalent urinary tract condition, is characterized by the development of crystals within the kidneys, which can lead to various clinical symptoms such as pain, hematuria, vomiting, and even renal failure, affecting more than 10% of the world's population\u003csup\u003e[1, 2]\u003c/sup\u003e. The pathogenesis of KSD is intricate, intricately intertwined with dietary habits, environmental factors, and metabolic states\u003csup\u003e[3, 4]\u003c/sup\u003e. Fortunately, the therapeutic landscape for KSD is well-established, encompassing conservative management, extracorporeal shockwave lithotripsy (ESWL), and surgical interventions. However, despite successful stone removal, the 5-year recurrence rate remains as high as 50%\u003csup\u003e[5, 6]\u003c/sup\u003e. Therefore, early identification and elimination of risk factors for KSD is the key to reducing the incidence and recurrence rate.\u003c/p\u003e \u003cp\u003eHigh intensity activities (HIA) usually refers to physical activity or exercise training that requires the body to perform high energy output and intense effort over a short period of time. This type of activity can significantly increase heart rate, respiratory rate and metabolic rate, which effectively promotes cardiorespiratory function and overall physical fitness\u003csup\u003e[7, 8]\u003c/sup\u003e. HIA has been widely used in competitive sports, physical training, rehabilitation and daily fitness\u003csup\u003e[9, 10]\u003c/sup\u003e. In recent years, significant progress has been made in the study of the relationship between HIA and cardiovascular health, metabolic syndrome, and diabetes. Multiple studies have shown that regular HIA helps to enhance cardiorespiratory function, improve blood glucose control, and reduce the risk of chronic diseases\u003csup\u003e[11, 12]\u003c/sup\u003e. Studies have shown that within a certain range, the prevalence of kidney stones decreases with the increase of exercise intensity\u003csup\u003e[13]\u003c/sup\u003e. However, other studies have shown that low-intensity exercise may reduce KSD, while high-intensity exercise may increase KSD, which may be related to the influence of high-intensity exercise on the metabolic environment in the body\u003csup\u003e[14]\u003c/sup\u003e. The mechanism of HIA's influence on KSD is still unclear, and its potential role needs further study.\u003c/p\u003e \u003cp\u003eThe purpose of this study was to investigate the association between high-intensity exercise and KSD by using data from the National Health and Nutrition Examination Survey (NHANES) database, so as to provide a new reference for clinical prevention and early intervention of KSD.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study population\u003c/h2\u003e \u003cp\u003eNHANES (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/index.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/nhanes/index.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was an annual study of the health of the population of the United States, and all its data were directly accessible. Written informed consent was obtained from all participants. Inclusion criteria were all subjects from 2007 to 2015, and exclusion criteria included (1) missing data on KSD and (2) missing data on variables. A final total of 6,642 subjects were recruited (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePreliminary screening of variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExcluding condition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50588\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRefused to answer \u0026amp; Missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44764\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRefused to answer \u0026amp; Missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ealcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know \u0026amp; missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6727\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehbp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know \u0026amp; missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ediabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know \u0026amp; missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know \u0026amp; missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6658\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDon't know \u0026amp; missing value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Definition of variables\u003c/h2\u003e \u003cp\u003eKSD was measured by asking \u0026lsquo;Have you ever had KSD?\u0026rsquo; Participants who answered \u0026lsquo;yes\u0026rsquo; were considered to have KSD (KIQ026) as an outcome. Age (DMDHRAGE) was a continuous variable; gender (RIAGENDR) was divided into male and female; race (RIDRETH1) was classified into four groups: non-Hispanic white, non-Hispanic black, Mexican American, and other; and educational status (DMDHREDU) was subdivided into three groups: high school, above high school, and below high school; economic status (INDFMPIR) was categorized into 3 groups based on Poverty Income Ratio (PIR): lowest (\u0026lt;\u0026thinsp;1.3), medium (1.3\u0026ndash;3.5) and highest (\u0026gt;\u0026thinsp;3.5-5); smoking status (SEQN) was subclassified into smokers (at least 100 cigarettes in a lifetime) and non-smokers (less than 100 cigarettes in a lifetime); and alcohol consumption (ALQ100/ALQ101) was categorized as the ability to have 12 drinks in a year; Body Mass Index (BMI, BMXBMI) computed as weight/height squared (kg/m\u003csup\u003e2\u003c/sup\u003e), sorted into \u0026lt;\u0026thinsp;20, 20\u0026ndash;25, 25\u0026ndash;30 and 30 kg/m\u003csup\u003e2\u003c/sup\u003e or more; presence of high blood pressure (BPQ020), diabetes (DIQ010), gout (MCQ160n\\MCQ160N) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDefinition of variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefinition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKIQ026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHave you ever had kidney stones?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2007\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMDHRAGE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edemo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRIDRETH1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edemo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRIAGENDR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edemo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDMDHREDU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edemo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eINDFMPIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEconomic situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edemo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEQN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALQ100\\ALQ101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrinking: 12 drinks a year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMXBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebmi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eexam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBPQ020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDIQ010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ediabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1999\u0026ndash;2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCQ160n\\\u003c/p\u003e \u003cp\u003eMCQ160N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eventilate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2007\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Risk correlation analysis\u003c/h2\u003e \u003cp\u003eTo understand the association between exposure factors and the risk of KSD, 2 adjusted models were constructed in which all covariates were assumed to interact with disease. 3 sequential multifactor glm regression models were constructed using the nhanesA package version 1.0.2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/package=nhanesA\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/package=nhanesA\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Model 1: exposure factor-high intensity activity (PAD615). Model 2: adjusted for age, race, gender. Model 3: further adjusted for educational status, economic status, smoking status, drinking status, BMI, hypertension, diabetes, gout (MCQ160n\\MCQ160N).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eFor between-group comparisons and description of baseline characteristics, we used two-sample t-test or Wilcoxon test for variables that were continuous, and chi-square test or Fisher exact test for categorical variables. Three logistic regression models were utilized to evaluate relationship between exposure factors (high intensity activity) and KSD, and adjusted odds ratio (OR) values and 95% confidence intervals were counted. Stratified analyses of age, gender, and BMI were conducted to further explore the correlation between exposure factors and the risk of KSD. Finally, after adjusting for covariates, the subjects' work characteristics (ROC) curves were analyzed with pROC package version 1.18.0\u003csup\u003e[15]\u003c/sup\u003e. Statistical analyses were carried out with R language. All tests were two-tailed with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline characteristics\u003c/h2\u003e \u003cp\u003eData from various clinical information on the number of people included were analyzed by t-test or chi-square test to determine if they were correlated with KSD, and the baseline statistical table showed that the exposure factor PAD615 (time spent in HIA) was chosen to have a significant differentiation of KSD (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline statistical tables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003elevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage (mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.77 (15.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.30 (13.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003erace (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137 (12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\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 \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 ( 3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e543 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83 (66.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 ( 7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 ( 8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther Race - Including Multi-Racial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 ( 6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 ( 7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egender (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302 (28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\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 \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759 (71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81 (64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eedu (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9-11th Grade (Includes 12th grade with no diploma)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (24.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.089\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 \u003cp\u003eCollege Graduate or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School Grad/GED or equivalent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 ( 8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 ( 6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School Grad/GED or Equivalent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess Than 9th Grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101 ( 9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 ( 3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome College or AA degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic\u003c/p\u003e \u003cp\u003e(mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.13 (1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23 (1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esmoke (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvery day\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e491 (46.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (45.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e449 (42.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 ( 6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ealcohol (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 ( 9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (12.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.391\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 \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e956 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109 (87.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egout (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1017 (95.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116 (92.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.182\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 \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 ( 4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 ( 7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ediabetes (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBorderline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 ( 1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 ( 4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\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 \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e952 (89.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 ( 8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehbp (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e703 (66.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (53.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\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 \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e358 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 ( 6.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 ( 4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\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 \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e589 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (68.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20_30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e399 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD615\u003c/p\u003e \u003cp\u003e(mean (SD))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188.78 (154.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e221.64 (164.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Association of HIA with KSD\u003c/h2\u003e \u003cp\u003eThe association analysis between exposure factor and outcome showed that HIA was significantly associated with KSD in all three models, with OR greater than 1 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The smoothed curves showed that short periods of HIA did not increase the risk of KSD, but over a certain period of time greatly increased the risk of KSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Stratified analyses of patients were performed by combining Model 3 to further confirm stability of correlation between exposure factors and KSD risk in various populations. The results showed that exposure factors and race, educational status, and gout were significantly associated with KSD in Model 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation analysis of exposure factors and outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eexposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003emodel1_OR(95%_CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emodel2_OR(95%_CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emodel3_OR(95%_CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePAD615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.001e\u0026thinsp;+\u0026thinsp;00( 1e\u0026thinsp;+\u0026thinsp;00-1.003e\u0026thinsp;+\u0026thinsp;00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.002e\u0026thinsp;+\u0026thinsp;00(1.001e\u0026thinsp;+\u0026thinsp;00-1.004e\u0026thinsp;+\u0026thinsp;00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.002e\u0026thinsp;+\u0026thinsp;00(1.001e\u0026thinsp;+\u0026thinsp;00-1.004e\u0026thinsp;+\u0026thinsp;00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep_value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.63E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.99E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.41E-03\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\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 HIA offered a favorable prediction of KSD\u003c/h2\u003e \u003cp\u003eThe ROC curve indicated that area under the curve (AUC) of model 3 for the prediction of the risk of KSD was \u0026gt;\u0026thinsp;0.7, suggesting that the prediction was relatively accurate (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It also revealed that the exposure factor could be a good predictor of the risk of the disease under the influence of various factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis cross-sectional study comprehensively investigated the association between HIA and KSD. Our research results show that PAD615 (HIA) is associated with the incidence of KSD (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). After adjusting for age, race, gender and other aspects in further risk association analysis, HIA still shows a significant relationship with KSD, and short-term HIA does not increase the risk of KSD. However, over a certain period of time, the risk of KSD is greatly increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOver the past 30 years, the incidence of KSD has nearly tripled in relative terms and increased by 5.6 percent in absolute terms. The increase in the prevalence of KSD was significant across all ages, genders, and ethnicities\u003csup\u003e[16]\u003c/sup\u003e. At present, the renal end treatment mainly includes conservative treatment, extracorporeal shock wave lithotomy and surgical treatment, and the recurrence rate of KSD is very high, which brings heavy economic burden to patients and society, and the annual healthcare expenditure of KSD in the United States exceeds 2\u0026nbsp;billion US dollars \u003csup\u003e[17\u0026ndash;19]\u003c/sup\u003e. In addition, KSD can also cause complications such as urinary tract infection, renal dysfunction, and even life-threatening sepsis, posing a serious threat to human health\u003csup\u003e[8, 20]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAt present, it has been established that dehydration and reduced urine volume are the most common risk factors for KSD\u003csup\u003e[21, 22]\u003c/sup\u003e. Increasing fluid intake and urine volume are important means to prevent stones \u003csup\u003e[23, 24]\u003c/sup\u003e. Notably, HIA inevitably leads to a sharp decrease in body moisture and dehydration, which may be an important reason for HIA as a risk factor for KSD. In addition to overt water loss, HIA also has a significant impact on metabolism in the body. HIA is bound to result in lactic acid accumulation. As an acidic substance, excessive accumulation of lactic acid in the body will decrease the pH value of the blood, which may lead to metabolic acidosis in severe cases\u003csup\u003e[25]\u003c/sup\u003e. In order to maintain the acid-base balance in the body, the kidneys remove more acidic substances, resulting in acidic urine. This change in pH can affect the solubility of certain minerals in the urine, thereby increasing the risk of stone formation \u003csup\u003e[26]\u003c/sup\u003e. In addition, in order to eliminate excessive hydrogen ions, the kidney will reduce the reabsorption of calcium and increase the excretion of calcium in the urine, and the increase of calcium content in the urine is another important reason for the formation of kidney stones\u003csup\u003e[27, 28]\u003c/sup\u003e. Therefore, HIA may promote the formation of KSD by affecting water and electrolyte balance and acid-base balance.\u003c/p\u003e \u003cp\u003eA study on the acute effects of HIA on renal function shows that HIA can cause increased serum creatinine (SCr), indicating that HIA can cause transient subclinical dysfunction of renal function to a certain extent\u003csup\u003e[29]\u003c/sup\u003e. Animal experiments have shown that HIA can increase the accumulation of serum creatinine and glycogen in mouse kidneys, activate PI3K/AKT/mTOR signaling pathway, induce kidney injury and fibrosis, and kidney injury can also lead to increased risk of kidney stones\u003csup\u003e[30]\u003c/sup\u003e. Other studies have shown that HIA can lead to the early significant increase of creatine kinase(CK), myoglobin, SCr, microalbuminuria and urine biomarkers indicating renal tubule injury, suggesting the occurrence of kidney injury\u003csup\u003e[31]\u003c/sup\u003e, and kidney injury and dysfunction promote the nucleation, aggregation and retention of urine crystals in the kidney. It may also produce ineffective crystallization modulators and local supersaturated areas of the mesenchyma, thereby affecting crystallization in the urine and promoting the development of kidney stones\u003csup\u003e[32]\u003c/sup\u003e. Therefore, it is speculated that HIA may promote the development of KSD by causing kidney injury or renal dysfunction.\u003c/p\u003e \u003cp\u003eOther studies have found that HIA is associated with oxidative stress, depending on the pattern, intensity, and duration of exercise, excessive HIA can lead to increased oxidative stress\u003csup\u003e[33]\u003c/sup\u003e. Structured high-intensity interval training (HIIT) generally improves overall and skeletal muscle metabolic health in different populations, however, if the accumulation of fatigue is not solved, it will cause oxidative stress disorder, and eventually lead to endocrine disorders, immune disorders, systemic inflammation and other adverse consequences \u003csup\u003e[34]\u003c/sup\u003e. Previous studies have shown that renal crystal deposition is related to the production of reactive oxygen species (ROS) and the activation of inflammasome, and urine supersaturation promotes plaque formation and calcium stone formation in kidney Randall by inducing ROS production and oxidative stress\u003csup\u003e[35]\u003c/sup\u003e. Oxidative stress can increase the risk of stone formation, and the inflammatory response generated during the formation of kidney stones further aggravates oxidative stress and forms a harmful cycle\u003csup\u003e[36]\u003c/sup\u003e. A study showed that the level of malondialdehyde (MDA), a marker of oxidative stress in KSD, was positively correlated with the level of oxalate in red blood cells and negatively correlated with the activity of antioxidant protein in red blood cells, indicating that oxidative stress of red blood cells may lead to renal tubule damage and stone accumulation in patients\u003csup\u003e[37]\u003c/sup\u003e. In animal experiments, it was also found that oxidative stress injury was related to the formation of kidney stones, and a high-sodium diet in mice would cause oxidative stress injury and loss of anti-crystallization defense, thus causing a large number of crystals formation in the kidney\u003csup\u003e[38]\u003c/sup\u003e. Therefore, excessive HIA may lead to the development of KSD through kidney injury and oxidative stress.\u003c/p\u003e \u003cp\u003eOur research has several advantages. We first provide evidence of a relationship between HIA and KSD in a large, cross-sectional, and well-developed dataset. In addition, we performed multivariate logistic analyses and sensitivity analyses adjusted for potential confounders to provide robust associations. This study provides evidence that HIA is a risk factor for KSD and needs attention.\u003c/p\u003e \u003cp\u003eNevertheless, some limitations should be considered. First, the cross-sectional design of NHANES suggests that no causal relationship can be established. Second, interview forums used for data collection can lead to potential bias. Third, some asymptomatic KSD patients are not physically examined and are missed in the database. Finally, there are unobserved confounding factors that may be missed. In conclusion, this study points out that HIA can be used as a predictor of KSD occurrence, providing ideas and strategies for early detection and elimination of risk factors for KSD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the grant from the project of Young and middle-aged backbone of The Affiliated Hospital of Youjiang Medical University for Nationalities (#Y20212613) and the Basic ability improvement project for young and middle-aged teachers of the Guangxi Zhuang Autonomous Region（#2023KY0551）.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFengwei Nong\u0026nbsp;and Zhengfang Liang\u0026nbsp;contributed equally to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJinan University, Guangzhou, Guangdong Province, China\u003c/p\u003e\n\u003cp\u003eDepartment of Renal Diseases, Affiliated Hospital of Youjiang Medical University for Nationalites, Baise, Guangxi, China\u003c/p\u003e\n\u003cp\u003eFengwei Nong\u0026amp;Jie Wang\u003c/p\u003e\n\u003cp\u003eDepartment of Urinary Surgery, Affiliated Hospital of Youjiang Medical University for Nationalites, Baise, Guangxi, China\u003c/p\u003e\n\u003cp\u003eKey Laboratory of Clinical Diagnosis and Treatment Research of High Incidence Diseases in Guangxi, China\u003c/p\u003e\n\u003cp\u003eZhengfang Liang, Runmin Chen\u0026amp;Yongping Huang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJie Wang and Yongping Huang conceived the study, Fengwei Nong and Zhengfang Liang collected and analyzed the data and draw the manuscript, Runmin Chen assisted in extracting and analyzing the data. All authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Jie Wang or Yongping Huang\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES was approved by the NCHS Research Ethics Review Board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants in the NHANES survey have signed a consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHoffman A, Braun MM, Khayat M. Kidney Disease: Kidney Stones[J]. 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PLoS One, 2015; 10(8): e0134764.\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":"kidney stone disease, high intensity activities, NHANES, association","lastPublishedDoi":"10.21203/rs.3.rs-5305949/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5305949/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eKidney stone disease (KSD) occurs in a wide range of ages and is influenced by multiple factors. Early detection and elimination of risk factors for KSD can effectively reduce the incidence of KSD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this research, we included KSD participants from the National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2015. Baseline characteristics of the participants were investigated using Student's t-tests and chi-square tests. Subsequently, the relationship between high intensity activities (HIA) and KSD was investigated through multifactor glm regression modeling. In addition, the linear relationship between them was explored by smoothing curves. Finally, the predictive performance of HIA on KSD was explored based on receiver operating characteristic (ROC) curves.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAt first, 6,642 subjects were finally recruited for this study. The baseline statistical table showed that the exposure factor (time spent in HIA) was chosen to have a significant differentiation for KSD. In addition, HIA was significantly associated with KSD in all three models, with OR greater than 1 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The smoothed curves showed that short periods of HIA did not increase the risk of KSD, but over a certain period of time greatly increased the risk of KSD. Stratified analysis results showed that exposure factors and race, educational status, and gout were significantly associated with KSD in Model 3. Eventually, ROC curve indicated the prediction for HIA to KSD was relatively accurate.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study revealed a link between HIA and KSD, with HIA over a certain period of time greatly increasing the risk of KSD.\u003c/p\u003e","manuscriptTitle":"The relationship between high intensity activities and kidney stone: A cross-sectional survey of NHANES","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-13 06:27:16","doi":"10.21203/rs.3.rs-5305949/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":"a17db138-2b02-4d2a-b83c-4f78262b1aa9","owner":[],"postedDate":"November 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-06T09:53:57+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-13 06:27:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5305949","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5305949","identity":"rs-5305949","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}