Association of nocturia with estimated glomerular filtration rate: a cross-sectional study from the NHANES 2005-2018

Association of nocturia with estimated glomerular filtration rate: a cross-sectional study from the NHANES 2005-2018 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association of nocturia with estimated glomerular filtration rate: a cross-sectional study from the NHANES 2005-2018 Jianling Song, Ben Ke, Xiangdong Fang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2259774/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Aug, 2023 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract Background Nocturia is a manifestation of systemic disease, of which chronic kidney disease is an independent predictor of nocturia because of its osmotic diuretic mechanism. However, to our knowledge, previous studies have not examined the relationship between nocturia and eGFR. Objective The purpose of this study was to assess the association between nocturia exposure and eGFR in the general US population. Methods Our study was a cross-sectional examination of 12,265 regular Americans who took part in the rvey NHANES between 2005 and 2018. After controlling for gender, age, race, fasting blood glucose, glycosylated hemoglobin, ALT, AST, TG, CHOL, HDL, LDL, BMI, diabetes, hypertension, alcohol consumption, tobacco use and PHQ9 score, a multiple regression analysis was performed to determine the association between nocturia and eGFR. Covariate-specific hierarchical analysis and interaction testing were performed. A sensitivity analysis was then conducted between the CKD group, the non-CKD group, and the various CKD prognostic risk groups. Results Multiple regression analysis showed that the frequency of nocturia increased by 1 time, and eGFR decreased 2.0 mL/min/1.73m 2 (95%CI: -2.4, -1.7). Compared with no nocturia, the decrease of eGFR was the most significant 4 times per night (95%CI: -10.7, -5.4). Our results remained stable in the CKD and non-CKD groups. Within all CKD prognostic risk groups, only the moderately increased risk and low-risk groups had comparable results. Conclusions Increased frequency of nocturia was associated with a decrease in eGFR, regardless of the diagnosis of CKD. However, no correlation between nocturia and eGFR was observed in very high risk and high risk groups. Health sciences/Diseases Health sciences/Nephrology Nocturia eGFR Chronic kidney disease CKD prognostic risk NHANES Figures Figure 1 Figure 2 1. Introduction The International Continence Society (ICS) defined nocturia as the number of times urine is passed during the main sleep period. Having woken to pass urine for the first time, each urination must be followed by sleep or the intention to sleep[1]. The frequency of nocturnal polyuria was 31.5% among men and 38.5% among women among individuals over 30 in the United States[2]. There is an extremely high incidence of nocturia among adults. Nevertheless, nocturia is undervalued by both patients and physicians. According to research conducted in Taiwan[3], just 25% of women with two or more nocturnal voids sought medical attention and only 63% of women who saw a physician were provided therapy. According to reports[4], nocturia more than 2 times accounts for 85.3% of elderly women and is indicative of poor female health. In elderly women, nocturia is connected with sleeplessness, weakness, urine incontinence, and falls. Increased severity of nocturia also was associated with worse quality of life[5]. Nocturia was also connected with a higher likelihood of depressed symptoms[6, 7]. Besides, cardiovascular disease was substantially connected with the prevalence of nocturia, and the risk for cardiovascular disease increased as nocturia severity increases[8]. Importantly, moderate and severe symptoms of the lower urinary tract are possible mortality risk factors[9]. A review on the Kidney Disease Quality of Life (KDQOL-36) identifies increased urination (including nocturia) as a prominent symptom in patients with chronic kidney disease stages 2-3b[10]. Nocturia may be influenced by renal function, diurnal changes in arginine vasopressin (AVP) production, sex, and old age[11]. However, the influence of nocturia on eGFR has received little attention. Therefore, we will investigate the relationship between nocturia and eGFR in this research. Methods 2.1. Study population We investigated National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2018, the study years for which information was available on nocturia frequency, the presence or absence of an enlarged prostate, and renal outcomes. Our studies included the frequency of nocturia, the estimated glomerular filtration rate, and the ACR. The flowchart is shown in Supplementary figure 1. Only participants with complete data for all variables (race/ethnicity, gender, age, blood glucose, HbA1c, TG, CHOL, HDL, LDL, uric acid, eGFR, BMI), previous medical history (hypertension, diabetes, drinking and smoking) and psychological factor (PHQ9) were included in the study. Notably, all individuals with an enlarged prostate were omitted. The International Continence Society (ICS) defines nocturia as awakening during the major sleep hours to urinate in 2018[12]. Since all data is available to the public and completely anonymous, no ethical review is necessary. This report was written in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology(STROBE) reporting guidelines for cross-sectional research[13]. 2.2 Measurement and definition of nocturia Nocturia data for each participant was obtained from NHANES questionnaire data about ‘How many times urinate in night?’ Research about examining the relationship between nocturia frequency and bother and health-related quality of life (HRQoL)[14],the majority of individuals experience discomfort when the number of nocturia episodes is two, and moderate or severe discomfort when the number is three or more. Therefore, we divided the individuals into two groups depending on the number of nocturia episodes: those with nocturia (nocturia≥2) and those without (nocturia<2). 2.3 Measurement of eGFR eGFR is not directly available in the NHANES database. Therefore，the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) [15] equation was used to calculate eGFR. Levey[15] aggregated information from 10 studies and established a novel formula, CKD-EPI equation, for estimating GFR from serum creatinine. The equation was verified using data from 16 studies, revealing that it is more accurate and less biased than the commonly used MDRD equation, particularly when calculating eGFR ≥ 60 mg/min. 2.4 Covariates Information on participants’ ages, sexes, and races/ethnicities was gathered by NHANES. We used the categories of non-Hispanic white, non-Hispanic black, Mexican American and other race/ethnicity to guarantee uniformity throughout all NHANES cycles. Measurements including height, weight, and blood pressure were taken during the survey’s physical examination phase. Blood and urine samples are taken by medical professionals and sent to testing facilities. Fasting blood glucose, HAB1C, biochemical indicators (ALT, AST, Cr, UA), blood lipids (TG, CHOL, LDL, HDL), ACR and PHQ9 score were all collected for this investigation. Hypertension was diagnosed as 3 consecutive measurements of systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg and taking prescription for hypertension and ever been told by a doctor or other health professional that you/she/he had hypertension. Diabetes was diagnosed as doctor told you have diabetes and taking diabetic pills to lower blood sugar. Extracting the answer to this question ‘In the past 12 months, on those days that “you/SP drank alcoholic beverages, on the average, how many drinks did you/he/she have?” and “days have 5 or more drinks/past 12 month” and “days per week, month, year?” and “Had at least 12 alcohol drinks/lifetime?” Drinking severity was defined[16] as (1) heavy alcohol user: ≥3 drinks per day for female；≥4 drinks per day for male；binge drinking on 5 or more days per month (2) moderate alcohol user: ≥2 drinks per day for female；≥3 drinks per day for male；binge drinking ≥2 days per month. (3) mild alcohol user: ≥1 drinks per day for female；≥2 drinks per day for male. (4) non-drinking was defined as answering no to the question “Had at least 12 alcohol drinks/lifetime?” Smoking was defined as answering yes to the question “Smoked at least 100 cigarettes in life?” or answering “every day”, “some days” to the question “Do you now smoke cigarettes?”. Alternatively described as not smoking. An assessment of depressive symptoms was conducted using the 9-item Patient Health Questionnaire (PHQ-9), which includes nine items based on DSM-IV symptoms of depression[17]. Clinically relevant depressions were considered those with PHQ-9 total scores of 10 or higher in this study[18]. 2.5 Statistical analysis Interview weights(wtin2yr), test weights(wtmec2yr), and subgroup weights are among the sample weights included in the NHANES data release file. The principle used is the “the lowest common denominator”. Fasting blood glucose sample weights were used as provided by NHANES for combining weights from all 8 cycles, following the NHANES analytic guidelines: http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm . Continuous variables are described by mean and standard deviation (if normally distributed), otherwise by median and interquartile range; group comparisons are made using the t-test (if normally distributed) or the Mann-Whitney test (if not normally distributed); and categorical variables are described as percentages. Using multivariate logistic regression, the link between nocturia and eGFR and ACR was determined. Adjustments were made to the final model for gender, age, race, fasting blood glucose, glycosylated hemoglobin, ALT, AST, TG, CHOL, LDL, HDL, uric acid, smoking history, diabetes history, and hypertension history. Sensitivity analyses were conducted in accordance with the diagnosis of CKD and its prognostic risk. A hierarchical analysis was carried out on the categorical variable number of nocturia. Additionally, stratified analyses and interaction tests for each covariate were carried out in order to comprehend how the impact of other factors on the relationship between nocturia and eGFR. The statistical software programs R (version 4.2.0) and Empower Stats (version 4.0) were used for all of the analyses. Statistical significance was assessed using a two-sided significance level of 0.05. Results Table 1 displays the demographic information and descriptive statistics by diagnosis of nocturia for the 12,265 NHANES individuals included in this investigation. The numbers of nocturia and non-nocturia in the study population were 3840 and 8425 and the proportion of non-Hispanic whites was 62.6% and 69.1%, respectively. Nocturia had higher levels of fasting blood glucose, ACR and MBI, as well as increased rates of smoking, diabetes, CKD and enlargement of hypertension. Those who nocturize have slightly lower eGFRs than those who do not. 3.1 The increase of nocturnal urination is association with the decrease of eGFR Without adjustment for other covariates, each increase in nocturia was associated with 3.5 mL/min/1.73m 2 (95%CI: -4.0, -3.0) decrease in eGFR (Supplementary table 1). After adjusting for multiple covariates, multiple regression analysis showed that every increase in the frequency of nocturia, the eGFR decreased by 2.0 mL/min/1.73m 2 (95%CI: -2.4, -1.7) (Table 2). Clearly, this conclusion has little clinical significance. Hence, We analyzed nocturia as a categorical variable. The findings of stratified analysis revealed that when nocturia occurred 4 times (95%CI: -10.7, -5.4) per night, the eGFR reduced considerably compared to the absence of nocturia, and this decline merited the attention of physicians (Table 2). Furthermore, interaction test findings indicate that hypertension increases the impact of nocturia on eGFR (Table 2 and Supplementary table 2). 3.2 Sensitivity analysis According to Kidney Disease Improving Global Outcomes (KDIGO) criteria[19], We divided the population into CKD and non-CKD groups by eGFR 30 mg/g. eGFR and ACR were used to evaluate the prognostic risk of CKD in participants. We discovered that eGFR reduced most substantially in individuals who urinated four times per night compared to those who did not urinate (95%CI: −9.7,−4.1) in the absence of CKD (Figure 1). In the CKD group, nocturia occurring between two and three times per night was related with a drop in eGFR compared to no nocturia (Figure 1). Furtherly, eGFR reduced slightly in both the moderately increased risk and low risk groups, figure 2 provides the findings. In the moderately increased risk and low risk groups, the frequency of nocturnal urination was related with a drop in eGFR. Despite this, the very high-risk group as well as the high-risk group did not observe correlation between nocturia and eGFR. Discussion In a representative sample of adult U.S. citizens using the NHANES database, we discovered an association between nocturia and eGFR. To our knowledge, this research is the broadest to show such a connection among Americans. Our findings are in line with the pathophysiological causes of nocturia, and the data suggests that nocturia may be a symptom of renal illness[11, 20, 21]. Numerous earlier research[22, 23] examined the causes of nocturia, but fewer focused on the relationship between nocturia and renal function. Nocturia has not been considered significant. Few women seek medical attention because they see nocturia symptoms as a natural part of aging[24]. Our findings raise the alarm for physicians and patients that nocturia is associated with lower eGFR. Regardless of CKD diagnosis, we discovered that nocturia was substantially related with decreased eGFR. Some evidence suggests a definite association between nighttime urination and kidney function. Empirical evidence[25] suggests that when renal function declines, the capacity to concentrate urine diminishes, creating nocturnal polyuria as an early sign of CKD. Some scientists[22] believe that osmotic diuresis, not free-water diuresis, is responsible for nocturnal polyuria and renal impairment in CKD. In addition, in individuals with chronic kidney illness, nocturia, which may suggest reduced renal tubular function, is linked to nondipping, and this association seems to be mediated by increased nocturnal activity[26]. Although previous studies have shown a link between nighttime urination and renal disease, ours is the first to examine the correlation between nocturia and eGFR. As a result, this might serve as a helpful reminder to clinicians to pay attention to patients who report experiencing nocturia symptoms once or many times per night. Our findings suggest that nocturia is linked to lower eGFR, particularly in those with undiagnosed CKD and those at low to moderately increased risk of CKD prognosis, and serve as a reminder to pay close attention to nocturia, particularly to eGFR fluctuations in the normal range or mild abnormalities. However, The sensitivity analysis revealed that our findings were inapplicable when CKD prognostic risk was separated into very high risk and high risk categories. This indicates that the association between nocturia and eFGR vanishes when renal function is reduced to a certain degree. Numerous disorders are connected to nocturia. The research indicated a 39% increase in nocturia among obese individuals with a BMI more than 30 kg/m 2 compared to non-obese individuals[27]. Second, those with diabetes were 49% more likely to have nocturia[28]. Moreover, nocturia is strongly associated with advancing age[29]. Only 0.4% of adults under the age of 40 have nocturia, compared to 11.5% of those over the age of 60[29]. Additionally, men with normotension were 39% less likely than untreated hypertensive patients to report nocturia[30].Therefore, risk factors for nocturia include aging, hypertension, diabetes, and obesity[27, 28, 31, 32], which all contribute to chronic renal disease[33-36]. However, we conducted an interaction study of variables with nocturia to validate their impact on the result, and it revealed that hypertension alone substantially impacted the association between nocturia and eGFR. because nocturia may result from hypertensive natriuresis[37]. Our research offers several benefits. Initially, the population-based strategy, multistage probability sampling, and high sample size all contributed to the generalizability of our results. Secondly, we explored for the first time the relationship between nocturia and eGFR. Finally, based on the impact of other factors on nocturia, we stratified them and evaluated their interactions with nocturia to propose a potential mechanistic explanation for the involvement of nocturia in renal function. The limitations of our investigation must also be noted. Due to the cross-sectional design of our investigation, we were only able to establish the association between nocturia exposure and eGFR, but not the causative evidence. Besides, When the prognostic risk of CKD is very high or high, which may be brought on by the relatively small number of individuals in these two categories, our result is not relevant. In order to get more precise findings, we want to undertake a bigger sample size research in these two groups in the future. Conclusion Increased frequency of nocturia was associated with a decrease in eGFR, regardless of the diagnosis of CKD. However, no correlation between nocturia and eGFR was observed very high risk and high risk groups. Declarations Conflicts of interest: Authors declare no conflicts of interest. Funding: This work was supported by Natural Science Foundation of China (no. 82160143) and Kidney Disease Engineering Research Center of Jiangxi Province (no. 20164BCD40095) Author contribution: Research idea and study design and data acquisition: Xiangdong Fang; data analysis/interpretation and statistical analysis：Jianling Song；supervision or mentorship: Ben Ke. Author initials takes responsibility that this study has been reported honestly, accurately and transparently, and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. Data availability statement All data generated or analysed during this study are included in this published article and its supplementary information files. 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Tables Table 1 Baseline characteristics of study participants Unweighted Weighted Non-nocturia Nocturia Non-nocturia Nocturia Age (years) 45.0(32.0-60.0) 59.0(45.0-70.0) 44.0 (31.0 ,57.0) 55.0 (43.0 ,67.0) Sex (%) Female 49.2 56.4 49.4 57.1 Male 50.8 43.6 50.6 42.9 Race (%) Non-hispanic white 44.5 37.8 69.1 62.6 Non-hispanic black 17.1 26.2 9.1 16.4 Mexican american 15.0 16.0 8.3 8.9 Other 23.5 20.0 13.6 12.1 eGFR ( mL/min/1.73m 2 ) 99.7 (84.2-113.5) 90.4 (73.3-105.7) 98.8 (84.2 ,112.4) 91.2 (75.6 ,106.2) ACR (mg/g) 6.5 (4.3-11.6) 8.8 (5.3-20.3) 6.1 (4.2 ,10.5) 7.7 (4.8 ,15.6) Fasting blood glucose (mmol/L) 5.5 (5.2-6.0) 5.8 (5.3-6.5) 5.5 (5.2 ,5.9) 5.7 (5.2 ,6.4) HBA1C (%) 5.5 (5.2-5.8) 5.7 (5.4-6.1) 5.4 (5.2 ,5.7) 5.6 (5.3 ,6.0) ALT (U/L) 21.0 (16.0-28.0) 20.0 (15.0-27.0) 21.0 (16.0 ,28.0) 20.0 (16.0 ,27.0) AST (U/L) 22.0 (19.0-27.0) 22.0 (19.0-27.0) 22.0 (19.0 ,27.0) 22.0 (19.0 ,27.0) Uric acid (umol/L) 321.2 (267.7-374.7) 327.1 (267.7-386.6) 321.2 (267.7 ,374.7) 321.2 (261.7 ,380.7) TG (umol/L) 1.1 (0.8-1.6) 1.2 (0.8-1.7) 1.1 (0.8 ,1.6) 1.2 (0.8 ,1.7) TCHOL (umol/L) 4.9 (4.2-5.6) 4.9 (4.2-5.6) 4.9 (4.2 ,5.6) 4.9 (4.2 ,5.6) HDL (umol/L) 1.3 (1.1-1.6) 1.3 (1.1-1.6) 1.3 (1.1 ,1.6) 1.3 (1.1 ,1.7) LDL (umol/L) 2.9 (2.3-3.5) 2.8 (2.3-3.5) 2.9 (2.3 ,3.5) 2.8 (2.3 ,3.5) BMI (Kg/m 2 ) 27.5 (23.9-31.8) 29.2 (25.3-34.3) 27.4 (23.8 ,31.8) 29.1 (25.2 ,34.5) Drinking (%) Never 12.5 17.3 9.6 14.3 Mild 49.1 51.8 49.7 51.9 Moderate 16.6 13.3 18.4 15.3 Heavy 21.8 17.5 22.3 18.5 Smoking (%) No 57.4 52.3 57.7 50.9 Yes 42.6 47.7 42.3 49.1 Hypertension (%) No 64.9 41.7 68.0 46.8 Yes 35.1 58.3 32.0 53.2 Diabetes (%) No 90.1 77.8 92.8 82.1 Yes 9.9 22.2 7.2 17.9 CKD (%) No 87.2 74.1 89.7 79.1 Yes 12.8 25.9 10.3 20.9 CKD prognosis Very high risk 1.3 3.7 0.8 2.4 High risk 2.1 5.6 1.5 4.4 Moderately increased risk 9.4 16.6 8.1 14.1 Low risk 87.2 74.1 89.7 79.1 PHQ9 score <10 93.7 85.8 94.5 86.5 ≥10 6.3 14.2 5.5 13.5 HBA1C: Hemoglobin A1C; ALT: glutamic pyruvic transaminase; AST: glutamic oxaloacetic transaminase; TG: triglyceride; CHOL: cholesterol; HDL: High-density lipoprotein; LDL: Low density lipoprotein; BMI: body mass index; eGFR: estimated glomerular filtration rate; ACR: albumin to creatinine ratio; Table 2 Relationship between Nocturia and eGFR in study population Outcome Crude model β (95% CI) P value Model I β (95% CI) P value Model II β (95% CI) P value Model II& β (95% CI) P value Nocturia -3.5 (-3.9, -3.1) <0.001 0.3 (0.0, 0.5) 0.048 -2.0 (-2.4, -1.7) <0.001 -2.6 (-3.0, -2.3) <0.001 0 0 0 0 0 1 -5.5 (-6.4, -4.6) <0.001 1.0 (0.4, 1.6) 0.002 -3.3 (-4.1, -2.6) <0.001 -4.1 (-4.9, -3.3) <0.001 2 -9.3 (-10.5, -8.2) <0.001 1.4 (0.5, 2.2) 0.001 -5.6 (-6.6, -4.5) <0.001 -7.2 (-8.2, -6.1) <0.001 3 -11.4 (-13.1, -9.7) <0.001 1.7 (0.4, 2.9) 0.007 -6.2 (-7.7, -4.7) <0.001 -8.0 (-9.6, -6.5) <0.001 4 -13.0 (-16.0, -10.0) <0.001 0.6 (-1.5, 2.8) 0.559 -8.0 (-10.7, -5.4) <0.001 -10.1 (-12.9, -7.4) <0.001 ≥5 -9.9 (-13.3, -6.4) <0.001 -2.0 (-4.4, 0.4) 0.108 -6.4 (-9.4, -3.3) <0.001 -8.3 (-11.4, -5.2) <0.001 Crude model adjust for: None ;Model I adjust for: sex; age; race；Model II adjust for: hypertrophy of prostate; fasting blood glucose; Hemoglobin A1C; glutamic pyruvic transaminase; glutamic oxaloacetic transaminase; uric acid; triglyceride; cholesterol; high-density lipoprotein; low density lipoprotein; sex; age; race; drinking; smoking; hypertension; body mass index; diabetes; Model II& Adjusted other variables except hypertension. Additional Declarations No competing interests reported. Supplementary Files Flowchart.pdf rawdata.txt supplementfigure1.docx supplementtable1.docx supplementtable2.docx Cite Share Download PDF Status: Published Journal Publication published 25 Aug, 2023 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Major revision 26 May, 2023 Reviews received at journal 14 May, 2023 Reviewers agreed at journal 06 May, 2023 Reviewers agreed at journal 06 May, 2023 Reviewers invited by journal 02 May, 2023 Editor assigned by journal 02 May, 2023 Editor invited by journal 14 Nov, 2022 Submission checks completed at journal 14 Nov, 2022 First submitted to journal 10 Nov, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2259774","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":152004256,"identity":"f6db8d95-1886-4aee-b2cc-bf0f5d02004a","order_by":0,"name":"Jianling Song","email":"","orcid":"","institution":"Medical College of Nanchang University, Nanchang of Jiangxi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jianling","middleName":"","lastName":"Song","suffix":""},{"id":152004259,"identity":"69a53322-3f2a-49b3-a81b-4f66efe133b5","order_by":1,"name":"Ben Ke","email":"","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University, Nanchang of Jiangxi","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ben","middleName":"","lastName":"Ke","suffix":""},{"id":152004260,"identity":"56cf1aef-b94b-4f5c-8f23-fdf74335c978","order_by":2,"name":"Xiangdong Fang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYDACZhDBBmIcABIVEnL8DIwNRGphSwASZyyMJRsIaWFA1sLYVpG44QABxQbHmZ89/FJmkyfvBmKckTA2Pn+47cEPBjs5XRyWSTazmRvLnEsrNjwGYgD9YnYjsd2whyHZ2AyHdfzMDGbSkm2HEzfObzCTlgDaYnaDsU2Ch+FA4jYcWtiY2b9BtLSBGRKJm/sPtkn+waOFn5nHTPIjUMt8NjBDInEDQ2KbND5bJJt5yqQZzqUlbmADMYAOk7gB1CJjgNsvBuePb5P8UWaTOL+NHcioqJPj7z/+TPJNhZ0cLi0gwMwD0nsAyoAahVs5CDD+ABLyDVDGKBgFo2AUjAJ0AACONlqmkvKihwAAAABJRU5ErkJggg==","orcid":"","institution":"The Second Affiliated Hospital of Nanchang University, Nanchang of Jiangxi","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiangdong","middleName":"","lastName":"Fang","suffix":""}],"badges":[],"createdAt":"2022-11-10 14:44:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2259774/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2259774/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-023-39448-0","type":"published","date":"2023-08-25T15:02:26+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":29201147,"identity":"80b505ad-f391-4106-9bc0-badffc6e1c04","added_by":"auto","created_at":"2022-11-17 17:13:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40554,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot showing the association of nocturia (6 categories) with eGFR in CKD and non-CKD populations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the analysis were adjusted for sex; age; race; hypertrophy of prostate; fasting blood glucose; Hemoglobin A1C; glutamic pyruvic transaminase; glutamic oxaloacetic transaminase; uric acid; triglyceride; cholesterol; high-density lipoprotein; low density lipoprotein; drinking; smoking; PHQ9 score\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/5f876c80298d17a0d4cedad9.png"},{"id":29201148,"identity":"fb8975f2-a740-4453-9568-b05c9e1622e0","added_by":"auto","created_at":"2022-11-17 17:13:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":48330,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plot showing the association of nocturia (6 categories) with eGFR in varying degrees of CKD prognostic risk\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the analysis were adjusted for sex; age; race; hypertrophy of prostate; fasting blood glucose; Hemoglobin A1C; glutamic pyruvic transaminase; glutamic oxaloacetic transaminase; uric acid; triglyceride; cholesterol; high-density lipoprotein; low density lipoprotein; drinking; smoking; PHQ9 score\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/29130fa8aeb6e281faf579f0.png"},{"id":42781170,"identity":"970b178e-70c4-428a-bfb2-f2f6c885fe3d","added_by":"auto","created_at":"2023-09-07 15:08:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1335261,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/0432644b-70a6-4916-99fa-c2d26a80ff22.pdf"},{"id":29201149,"identity":"bc3e84d2-4ae4-454a-99ce-4caf1092f8f7","added_by":"auto","created_at":"2022-11-17 17:13:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":417444,"visible":true,"origin":"","legend":"","description":"","filename":"Flowchart.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/d1549bca43099ef98627cafe.pdf"},{"id":29201151,"identity":"a1ae0d9a-8019-4bf4-bb71-709164343e67","added_by":"auto","created_at":"2022-11-17 17:13:48","extension":"txt","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1575236,"visible":true,"origin":"","legend":"","description":"","filename":"rawdata.txt","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/b9649a97dcd53aa263fdd8c6.txt"},{"id":29201933,"identity":"4769ad14-85a6-4ff7-8f8e-5190fa5febca","added_by":"auto","created_at":"2022-11-17 17:21:48","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":323820,"visible":true,"origin":"","legend":"","description":"","filename":"supplementfigure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/21e44e07181737139ad4b831.docx"},{"id":29201932,"identity":"e0437974-5424-432d-83d6-6bfce9a373e0","added_by":"auto","created_at":"2022-11-17 17:21:48","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":20780,"visible":true,"origin":"","legend":"","description":"","filename":"supplementtable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/10dce56b0f0d2a8e044aa3d3.docx"},{"id":29201153,"identity":"b2514560-7041-4219-82d9-631da30fe85f","added_by":"auto","created_at":"2022-11-17 17:13:48","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":24064,"visible":true,"origin":"","legend":"","description":"","filename":"supplementtable2.docx","url":"https://assets-eu.researchsquare.com/files/rs-2259774/v1/b188be9a1d3bcd09d09bcf27.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of nocturia with estimated glomerular filtration rate: a cross-sectional study from the NHANES 2005-2018","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe International Continence Society (ICS) defined nocturia as the number of times urine is passed during the main sleep period. Having woken to pass urine for the first time, each urination must be followed by sleep or the intention to sleep[1]. The frequency of nocturnal polyuria was 31.5% among men and 38.5% among women among individuals over 30 in the United States[2]. There is an extremely high incidence of nocturia among adults. Nevertheless, nocturia is undervalued by both patients and physicians. According to research conducted in Taiwan[3], just 25% of women with two or more nocturnal voids sought medical attention and only 63% of women who saw a physician were provided therapy. According to reports[4], nocturia more than 2 times accounts for 85.3% of elderly women and is indicative of poor female health. In elderly women, nocturia is connected with sleeplessness, weakness, urine incontinence, and falls. Increased severity of nocturia also was associated with worse quality of life[5]. Nocturia was also connected with a higher likelihood of depressed symptoms[6, 7]. Besides, cardiovascular disease was substantially connected with the prevalence of nocturia, and the risk for cardiovascular disease increased as nocturia severity increases[8]. Importantly, moderate and severe symptoms of the lower urinary tract are possible mortality risk factors[9]. A review on the Kidney Disease Quality of Life (KDQOL-36) identifies increased urination (including nocturia) as a prominent symptom in patients with chronic kidney disease stages 2-3b[10]. Nocturia may be influenced by renal function, diurnal changes in arginine vasopressin (AVP) production, sex, and old age[11]. However, the influence of nocturia on eGFR has received little attention. Therefore, we will investigate the relationship between nocturia and eGFR in this research.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1. Study population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2018, the study years for which information was available on nocturia frequency, the presence or absence of an enlarged prostate, and renal outcomes. Our studies included the frequency of nocturia, the estimated glomerular filtration rate, and the ACR. The flowchart is shown in Supplementary figure 1. Only participants with complete data for all variables (race/ethnicity, gender, age, blood glucose, HbA1c, TG, CHOL, HDL, LDL, uric acid, eGFR, BMI), previous medical history (hypertension, diabetes, drinking and smoking) and psychological factor (PHQ9) were included in the study. Notably, all individuals with an enlarged prostate were omitted. The International Continence Society (ICS) defines nocturia as awakening during the major sleep hours to urinate in 2018[12]. Since all data is available to the public and completely anonymous, no ethical review is necessary. This report was written in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology(STROBE) reporting guidelines for cross-sectional research[13].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Measurement and definition of nocturia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNocturia data for each participant was obtained from NHANES questionnaire data about \u0026lsquo;How many times urinate in night?\u0026rsquo; Research about examining the relationship between nocturia frequency and bother and health-related quality of life (HRQoL)[14],the majority of individuals experience discomfort when the number of nocturia episodes is two, and moderate or severe discomfort when the number is three or more. Therefore, we divided the individuals into two groups depending on the number of nocturia episodes: those with nocturia (nocturia\u0026ge;2) and those without (nocturia\u0026lt;2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Measurement of eGFR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eeGFR is not directly available in the NHANES database. Therefore，the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) [15] equation was used to calculate eGFR. Levey[15] aggregated information from 10 studies and established a novel formula, CKD-EPI equation, for estimating GFR from serum creatinine. The equation was verified using data from 16 studies, revealing that it is more accurate and less biased than the commonly used MDRD equation, particularly when calculating eGFR \u0026ge; 60 mg/min.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Covariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformation on participants\u0026rsquo; ages, sexes, and races/ethnicities was gathered by NHANES. We used the categories of non-Hispanic white, non-Hispanic black, Mexican American and other race/ethnicity to guarantee uniformity throughout all NHANES cycles. Measurements including height, weight, and blood pressure were taken during the survey\u0026rsquo;s physical examination phase. Blood and urine samples are taken by medical professionals and sent to testing facilities. Fasting blood glucose, HAB1C, biochemical indicators (ALT, AST, Cr, UA), blood lipids (TG, CHOL, LDL, HDL), ACR and PHQ9 score were all collected for this investigation.\u003c/p\u003e\n\u003cp\u003eHypertension was diagnosed as 3 consecutive measurements of systolic blood pressure \u0026ge; 140 mmHg or diastolic blood pressure \u0026ge; 90 mmHg and taking prescription for hypertension and ever been told by a doctor or other health professional that you/she/he had hypertension. Diabetes was diagnosed as doctor told you have diabetes and taking diabetic pills to lower blood sugar.\u003c/p\u003e\n\u003cp\u003eExtracting the answer to this question \u0026lsquo;In the past 12 months, on those days that \u0026ldquo;you/SP drank alcoholic beverages, on the average, how many drinks did you/he/she have?\u0026rdquo; and \u0026ldquo;days have 5 or more drinks/past 12 month\u0026rdquo; and \u0026ldquo;days per week, month, year?\u0026rdquo; and \u0026ldquo;Had at least 12 alcohol drinks/lifetime?\u0026rdquo; Drinking severity was defined[16] as (1) heavy alcohol user: \u0026ge;3 drinks per day for female；\u0026ge;4 drinks per day for male；binge drinking on 5 or more days per month (2) moderate alcohol user: \u0026ge;2 drinks per day for female；\u0026ge;3 drinks per day for male；binge drinking \u0026ge;2 days per month. (3) mild alcohol user: \u0026ge;1 drinks per day for female；\u0026ge;2 drinks per day for male. (4) non-drinking was defined as answering no to the question \u0026ldquo;Had at least 12 alcohol drinks/lifetime?\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eSmoking was defined as answering yes to the question \u0026ldquo;Smoked at least 100 cigarettes in life?\u0026rdquo; or answering \u0026ldquo;every day\u0026rdquo;, \u0026ldquo;some days\u0026rdquo; to the question \u0026ldquo;Do you now smoke cigarettes?\u0026rdquo;. Alternatively described as not smoking. \u003c/p\u003e\n\u003cp\u003eAn assessment of depressive symptoms was conducted using the 9-item Patient Health Questionnaire (PHQ-9), which includes nine items based on DSM-IV symptoms of depression[17]. Clinically relevant depressions were considered those with PHQ-9 total scores of 10 or higher in this study[18].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterview weights(wtin2yr), test weights(wtmec2yr), and subgroup weights are among the sample weights included in the NHANES data release file. The principle used is the \u0026ldquo;the lowest common denominator\u0026rdquo;. Fasting blood glucose sample weights were used as provided by NHANES for combining weights from all 8 cycles, following the NHANES analytic guidelines: http://www.cdc.gov/nchs/nhanes/nhanes_questionnaires.htm\u003cu\u003e.\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables are described by mean and standard deviation (if normally distributed), otherwise by median and interquartile range; group comparisons are made using the t-test (if normally distributed) or the Mann-Whitney test (if not normally distributed); and categorical variables are described as percentages. Using multivariate logistic regression, the link between nocturia and eGFR and ACR was determined. Adjustments were made to the final model for gender, age, race, fasting blood glucose, glycosylated hemoglobin, ALT, AST, TG, CHOL, LDL, HDL, uric acid, smoking history, diabetes history, and hypertension history. Sensitivity analyses were conducted in accordance with the diagnosis of CKD and its prognostic risk. A hierarchical analysis was carried out on the categorical variable number of nocturia. Additionally, stratified analyses and interaction tests for each covariate were carried out in order to comprehend how the impact of other factors on the relationship between nocturia and eGFR.\u003c/p\u003e\n\u003cp\u003eThe statistical software programs R (version 4.2.0) and Empower Stats (version 4.0) were used for all of the analyses. Statistical significance was assessed using a two-sided significance level of 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable 1 displays the demographic information and descriptive statistics by diagnosis of nocturia for the 12,265 NHANES individuals included in this investigation. The numbers of nocturia and non-nocturia in the study population were 3840 and 8425 and the proportion of non-Hispanic whites was 62.6% and 69.1%, respectively. Nocturia had higher levels of fasting blood glucose, ACR and MBI, as well as increased rates of smoking, diabetes, CKD and enlargement of hypertension. Those who nocturize have slightly lower eGFRs than those who do not.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 The increase of nocturnal urination is association with the decrease of eGFR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWithout adjustment for other covariates, each increase in nocturia was associated with 3.5\u0026nbsp;mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e (95%CI:\u0026nbsp;-4.0, -3.0) decrease in eGFR (Supplementary table 1). After\u0026nbsp;adjusting for multiple covariates, multiple regression analysis showed that every increase in the frequency of nocturia, the eGFR decreased by 2.0 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e (95%CI: -2.4, -1.7) (Table 2). Clearly, this conclusion has little clinical significance. Hence, We analyzed nocturia as a categorical variable. The findings of stratified analysis revealed that when nocturia occurred 4 times (95%CI: -10.7, -5.4) per night, the eGFR reduced considerably compared to the absence of nocturia, and this decline merited the attention of physicians (Table 2). Furthermore, interaction test findings indicate that hypertension increases the impact of nocturia on eGFR (Table 2 and\u0026nbsp;Supplementary table 2).\u003c/p\u003e\n\u003cp skip=\"true\"\u003e\u003cstrong\u003e3.2 Sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp skip=\"true\"\u003eAccording to Kidney Disease Improving Global Outcomes (KDIGO) criteria[19], We divided the population into CKD and non-CKD groups by eGFR \u0026lt; 60 mL/min/1.73m\u003csup\u003e2 \u003c/sup\u003eand ACR \u0026gt; 30 mg/g. eGFR and ACR were used to evaluate the prognostic risk of CKD in participants. We discovered that eGFR reduced most substantially in individuals who urinated four times per night compared to those who did not urinate (95%CI: \u0026minus;9.7,\u0026minus;4.1) in the absence of CKD (Figure 1). In the CKD group, nocturia occurring between two and three times per night was related with a drop in eGFR compared to no nocturia (Figure 1). Furtherly, eGFR reduced slightly in both the moderately increased risk and low risk groups, figure 2 provides the findings. In the moderately increased risk and low risk groups, the frequency of nocturnal urination was related with a drop in eGFR. Despite this, the very high-risk group as well as the high-risk group did not observe correlation between nocturia and eGFR.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn a representative sample of adult U.S. citizens using the NHANES database, we discovered an association between nocturia and eGFR. To our knowledge, this research is the broadest to show such a connection among Americans. Our findings are in line with the pathophysiological causes of nocturia, and the data suggests that nocturia may be a symptom of renal illness[11, 20, 21]. Numerous earlier research[22, 23]\u0026nbsp;examined the causes of nocturia, but fewer focused on the relationship between nocturia and renal function.\u0026nbsp;Nocturia has not been considered significant. Few women seek medical attention because they see nocturia symptoms as a natural part of aging[24]. Our findings raise the alarm for physicians and patients that nocturia is associated with lower eGFR.\u003c/p\u003e\n\u003cp\u003eRegardless of CKD diagnosis, we discovered that nocturia was substantially related with decreased eGFR. Some evidence suggests a definite association between nighttime urination and kidney function. Empirical evidence[25] suggests that when renal function declines, the capacity to concentrate urine diminishes, creating nocturnal polyuria as an early sign of CKD. \u0026nbsp;Some scientists[22] believe that osmotic diuresis, not free-water diuresis, is responsible for nocturnal polyuria and renal impairment in CKD. In addition, in individuals with chronic kidney illness, nocturia, which may suggest reduced renal tubular function, is linked to nondipping, and this association seems to be mediated by increased nocturnal activity[26]. Although previous studies have shown a link between nighttime urination and renal disease, ours is the first to examine the correlation between nocturia and eGFR. As a result, this might serve as a helpful reminder to clinicians to pay attention to patients who report experiencing nocturia symptoms once or many times per night.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Our findings suggest that nocturia is linked to lower eGFR, particularly in those with undiagnosed CKD and those at low to moderately increased risk of CKD prognosis, and serve as a reminder to pay close attention to nocturia, particularly to eGFR fluctuations in the normal range or mild abnormalities. However, The sensitivity analysis revealed that our findings were inapplicable when CKD prognostic risk was separated into very high risk and high risk categories. This indicates that the association between nocturia and eFGR vanishes when renal function is reduced to a certain degree.\u003c/p\u003e\n\u003cp\u003eNumerous disorders are connected to nocturia. The research indicated a 39% increase in nocturia among obese individuals with a BMI more than 30 kg/m\u003csup\u003e2\u003c/sup\u003e compared to non-obese individuals[27]. Second, those with diabetes were 49% more likely to have nocturia[28]. Moreover, nocturia is strongly associated with advancing age[29]. Only 0.4% of adults under the age of 40 have nocturia, compared to 11.5% of those over the age of 60[29]. Additionally, men with normotension were 39% less likely than untreated hypertensive patients to report nocturia[30].Therefore, risk factors for nocturia include aging, hypertension, diabetes, and obesity[27, 28, 31, 32], which all contribute to chronic renal disease[33-36]. However, we conducted an interaction study of variables with nocturia to validate their impact on the result, and it revealed that hypertension alone substantially impacted the association between nocturia and eGFR. because nocturia may result from hypertensive natriuresis[37].\u003c/p\u003e\n\u003cp\u003eOur research offers several benefits. Initially, the population-based strategy, multistage probability sampling, and high sample size all contributed to the generalizability of our results. Secondly, we explored for the first time the relationship between nocturia and eGFR. Finally, based on the impact of other factors on nocturia, we stratified them and evaluated their interactions with nocturia to propose a potential mechanistic explanation for the involvement of nocturia in renal function. The limitations of our investigation must also be noted. Due to the cross-sectional design of our investigation, we were only able to establish the association between nocturia exposure and eGFR, but not the causative evidence. Besides, When the prognostic risk of CKD is very high or high, which may be brought on by the relatively small number of individuals in these two categories, our result is not relevant. In order to get more precise findings, we want to undertake a bigger sample size research in these two groups in the future.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIncreased frequency of nocturia was associated with a decrease in eGFR, regardless of the diagnosis of CKD. However, no correlation between nocturia and eGFR was observed very high risk and high risk groups.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest:\u003c/strong\u003e Authors declare no conflicts of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was supported by Natural Science Foundation of China (no. 82160143) and Kidney Disease Engineering Research Center of Jiangxi Province (no. 20164BCD40095)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution:\u0026nbsp;\u003c/strong\u003eResearch idea and study design and data acquisition: Xiangdong Fang; data analysis/interpretation and statistical analysis：Jianling Song；supervision or mentorship: Ben Ke. Author initials takes responsibility that this study has been reported honestly, accurately and transparently, and accepts accountability for the overall work by ensuring that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHashim H, Blanker MH, Drake MJ, Djurhuus JC, Meijlink J, Morris V, Petros P, Wen JG, Wein A: \u003cstrong\u003eInternational Continence Society (ICS) report on the terminology for nocturia and nocturnal lower urinary tract function\u003c/strong\u003e. \u003cem\u003eNeurourology and urodynamics \u003c/em\u003e2019, 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population\u003c/strong\u003e. \u003cem\u003eAmerican journal of kidney diseases : the official journal of the National Kidney Foundation \u003c/em\u003e2014, \u003cstrong\u003e63\u003c/strong\u003e(3):349-353.\u003c/li\u003e\n\u003cli\u003eGeorgianos PI, Agarwal R: \u003cstrong\u003eHypertension in Chronic Kidney Disease (CKD): Diagnosis, Classification, and Therapeutic Targets\u003c/strong\u003e. \u003cem\u003eAmerican journal of hypertension \u003c/em\u003e2021, \u003cstrong\u003e34\u003c/strong\u003e(4):318-326.\u003c/li\u003e\n\u003cli\u003eMount PF, Juncos LA: \u003cstrong\u003eObesity-Related CKD: When Kidneys Get the Munchies\u003c/strong\u003e. \u003cem\u003eJournal of the American Society of Nephrology : JASN \u003c/em\u003e2017, \u003cstrong\u003e28\u003c/strong\u003e(12):3429-3432.\u003c/li\u003e\n\u003cli\u003eOhishi M, Kubozono T, Higuchi K, Akasaki Y: \u003cstrong\u003eHypertension, cardiovascular disease, and nocturia: a systematic review of the pathophysiological mechanisms\u003c/strong\u003e. \u003cem\u003eHypertension research : official journal of the Japanese Society of Hypertension \u003c/em\u003e2021, \u003cstrong\u003e44\u003c/strong\u003e(7):733-739.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Baseline characteristics of study participants\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnweighted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeighted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-nocturia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNocturia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-nocturia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNocturia\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003cstrong\u003e(years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.0(32.0-60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e59.0(45.0-70.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.0 (31.0 ,57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e55.0 (43.0 ,67.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-hispanic white\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-hispanic black\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMexican american\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eeGFR\u003c/strong\u003e\u003cstrong\u003e(\u003c/strong\u003e\u003cstrong\u003emL/min/1.73m\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e99.7 (84.2-113.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.4 (73.3-105.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e98.8 (84.2 ,112.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91.2 (75.6 ,106.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eACR (mg/g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.5 (4.3-11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.8 (5.3-20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.1 (4.2 ,10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.7 (4.8 ,15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFasting blood glucose\u003c/strong\u003e\u003cstrong\u003e(mmol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.5 (5.2-6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.8 (5.3-6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.5 (5.2 ,5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.7 (5.2 ,6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHBA1C\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.5 (5.2-5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.7 (5.4-6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.4 (5.2 ,5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.6 (5.3 ,6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eALT\u003c/strong\u003e\u003cstrong\u003e(U/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.0 (16.0-28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.0 (15.0-27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.0 (16.0 ,28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.0 (16.0 ,27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAST\u003c/strong\u003e\u003cstrong\u003e(U/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.0 (19.0-27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.0 (19.0-27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.0 (19.0 ,27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.0 (19.0 ,27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUric acid\u003c/strong\u003e\u003cstrong\u003e(umol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e321.2 (267.7-374.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e327.1 (267.7-386.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e321.2 (267.7 ,374.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e321.2 (261.7 ,380.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTG\u003c/strong\u003e\u003cstrong\u003e(umol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 (0.8-1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.2 (0.8-1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.1 (0.8 ,1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.2 (0.8 ,1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTCHOL\u003c/strong\u003e\u003cstrong\u003e(umol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.9 (4.2-5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.9 (4.2-5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.9 (4.2 ,5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.9 (4.2 ,5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL\u003c/strong\u003e\u003cstrong\u003e(umol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.3 (1.1-1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.3 (1.1-1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.3 (1.1 ,1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.3 (1.1 ,1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL\u003c/strong\u003e\u003cstrong\u003e(umol/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.9 (2.3-3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.8 (2.3-3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.9 (2.3 ,3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.8 (2.3 ,3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003cstrong\u003e(Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.5 (23.9-31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.2 (25.3-34.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.4 (23.8 ,31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.1 (25.2 ,34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.6\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMild\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e51.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeavy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e21.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e52.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57.7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e47.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e42.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e58.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.0\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e77.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCKD (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCKD prognosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVery high risk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.8\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.4\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh risk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerately increased risk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow risk\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e87.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e74.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e89.7\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79.1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePHQ9 score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;93.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;85.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e94.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e86.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eHBA1C: Hemoglobin A1C; ALT: glutamic pyruvic transaminase; AST: glutamic oxaloacetic transaminase; TG: triglyceride; CHOL: cholesterol; HDL: High-density lipoprotein; LDL: Low density lipoprotein; BMI: body mass index; eGFR: estimated glomerular filtration rate; ACR: albumin to creatinine ratio;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Relationship between\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eNocturia\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and eGFR in study population\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude model\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; (95% CI) P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;I\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; (95% CI) P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;II\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; (95% CI) P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u0026nbsp;II\u0026amp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta; (95% CI) P value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNocturia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.5 (-3.9, -3.1) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.3 (0.0, 0.5) 0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.0 (-2.4, -1.7) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-2.6 (-3.0, -2.3) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-5.5 (-6.4, -4.6) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.0 (0.4, 1.6) 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-3.3 (-4.1, -2.6) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-4.1 (-4.9, -3.3) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-9.3 (-10.5, -8.2) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.4 (0.5, 2.2) 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-5.6 (-6.6, -4.5) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-7.2 (-8.2, -6.1) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-11.4 (-13.1, -9.7) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.7 (0.4, 2.9) 0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-6.2 (-7.7, -4.7) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-8.0 (-9.6, -6.5) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-13.0 (-16.0, -10.0) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.6 (-1.5, 2.8) 0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-8.0 (-10.7, -5.4) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-10.1 (-12.9, -7.4) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp;\u0026ge;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-9.9 (-13.3, -6.4) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-2.0 (-4.4, 0.4) 0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-6.4 (-9.4, -3.3) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-8.3 (-11.4, -5.2) \u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCrude model\u0026nbsp;adjust for: None\u0026nbsp;;Model\u0026nbsp;I adjust for: sex; age; race；Model\u0026nbsp;II adjust for: hypertrophy of prostate;\u0026nbsp;fasting\u0026nbsp;blood glucose;\u0026nbsp;Hemoglobin A1C;\u0026nbsp;glutamic pyruvic transaminase;\u0026nbsp;glutamic oxaloacetic transaminase;\u0026nbsp;uric acid;\u0026nbsp;triglyceride;\u0026nbsp;cholesterol;\u0026nbsp;high-density lipoprotein;\u0026nbsp;low density lipoprotein; sex; age; race;\u0026nbsp;drinking; smoking;\u0026nbsp;hypertension;\u0026nbsp;body mass index;\u0026nbsp;diabetes;\u0026nbsp;Model\u0026nbsp;II\u0026amp; Adjusted other variables except hypertension.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Nocturia, eGFR, Chronic kidney disease, CKD prognostic risk, NHANES","lastPublishedDoi":"10.21203/rs.3.rs-2259774/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2259774/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNocturia is a manifestation of systemic disease, of which chronic kidney disease is an independent predictor of nocturia because of its osmotic diuretic mechanism. However, to our knowledge, previous studies have not examined the relationship between nocturia and eGFR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of this study was to assess the association between nocturia exposure and eGFR in the general US population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study was a cross-sectional examination of 12,265 regular Americans who took part in the rvey NHANES between 2005 and 2018. After controlling for gender, age, race, fasting blood glucose, glycosylated hemoglobin, ALT, AST, TG, CHOL, HDL, LDL, BMI, diabetes, hypertension, alcohol consumption, tobacco use and PHQ9 score, a multiple regression analysis was performed to determine the association between nocturia and eGFR. Covariate-specific hierarchical analysis and interaction testing were performed. A sensitivity analysis was then conducted between the CKD group, the non-CKD group, and the various CKD prognostic risk groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultiple regression analysis showed that the frequency of nocturia increased by 1 time, and eGFR decreased 2.0 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e (95%CI: -2.4, -1.7). Compared with no nocturia, the decrease of eGFR was the most significant 4 times per night (95%CI: -10.7, -5.4). Our results remained stable in the CKD and non-CKD groups. Within all CKD prognostic risk groups, only the moderately increased risk and low-risk groups had comparable results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIncreased frequency of nocturia was associated with a decrease in eGFR, regardless of the diagnosis of CKD. However, no correlation between nocturia and eGFR was observed in very high risk and high risk groups.\u003c/p\u003e","manuscriptTitle":"Association of nocturia with estimated glomerular filtration rate: a cross-sectional study from the NHANES 2005-2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-17 17:13:43","doi":"10.21203/rs.3.rs-2259774/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-05-26T06:59:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-05-15T01:26:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c47611c2-a44b-4fe9-b3a1-751961c71da0","date":"2023-05-07T03:37:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b6bbc076-d676-42ca-817c-1b9d207fcc2a","date":"2023-05-06T07:48:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-05-02T23:25:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-05-02T23:19:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-11-14T15:40:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-11-14T15:35:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2022-11-10T14:29:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"64e9032b-6eb4-4ede-acd5-f818b18fa67a","owner":[],"postedDate":"November 17th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":16957751,"name":"Health sciences/Diseases"},{"id":16957752,"name":"Health sciences/Nephrology"}],"tags":[],"updatedAt":"2023-09-07T15:06:04+00:00","versionOfRecord":{"articleIdentity":"rs-2259774","link":"https://doi.org/10.1038/s41598-023-39448-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2023-08-25 15:02:26","publishedOnDateReadable":"August 25th, 2023"},"versionCreatedAt":"2022-11-17 17:13:43","video":"","vorDoi":"10.1038/s41598-023-39448-0","vorDoiUrl":"https://doi.org/10.1038/s41598-023-39448-0","workflowStages":[]},"version":"v1","identity":"rs-2259774","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2259774","identity":"rs-2259774","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}