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Objective: This study aims to investigate how arthritis, including osteoarthritis and rheumatoid arthritis, affects the incidence of nocturia in adults aged 20–59. Methods: This study utilized data from the National Health and Nutrition Examination Survey from 2005 to 2020, involving 18 745 adults aged 20–59. Arthritis, including osteoarthritis and rheumatoid arthritis, was considered as the exposure factor, with nocturia as the outcome variable. We first compared the baseline characteristics of individuals with and without nocturia. The impact of arthritis on nocturia was assessed using weighted multivariate logistic regression models. To ensure the stability of the results, propensity score matching analysis and subgroup analyses were conducted. Results: The incidence of nocturia was approximately 22.31%, and the incidence of arthritis was about 15.32% (2871/18 745), with osteoarthritis accounting for 35.49% (1019/2871) and rheumatoid arthritis accounting for 20.20% (580/2871). Adjusted multivariate logistic regression analysis revealed that the risk of nocturia was increased by arthritis (odds ratio [OR] = 1.45, 95% confidence interval [CI]: 1.28–1.65, p < 0.0001), including osteoarthritis (OR = 1.45, 95% CI: 1.18–1.78, p < 0.001) and rheumatoid arthritis (OR = 1.51, 95% CI: 1.14–2.00, p = 0.004). After propensity score matching using nearest neighbor methods at a 1:1 ratio, this relationship still exists. Subgroup analyses showed no significant differences in the interactions between arthritis and the risk of nocturia across various factors, such as age, family income to poverty ratio, education level, body mass index, smoking status, hypertension, and diabetes. However, significant differences were observed across different sex groups and sleep trouble groups. Conclusions: This study revealed that arthritis, including osteoarthritis and rheumatoid arthritis, increased the risk of nocturia in adults under the age of 60. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to examine the association between blood lead levels and the prevalence of nocturia in American adults. Methods: We analyzed data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2020, focusing on individuals aged 20 years or older (n = 11,919). Blood lead levels were categorized into two groups (<2 µg/dL and ≥2 µg/dL), and the presence of nocturia was assessed based on questionnaire responses. We used multivariable logistic regression models to explore the association between blood lead levels and nocturia while adjusting for various covariates, including sex, ratio of family income to poverty (RIP), lipid profile, age, body mass index (BMI), race, citizenship, sleep trouble, diabetes, and hypertension. To verify whether certain covariates influence blood lead levels and the risk of nocturia, we conducted subgroup analyses. Results: Of the study participants, 31.70% reported experiencing nocturia. Individuals with higher blood lead levels (≥2 µg/dL) exhibited a higher likelihood of experiencing nocturia compared to those with lower levels (<2 µg/dL) in all three models (Model 1: OR 1.46, 95% CI 1.29–1.66, p < 0.0001; Model 2: OR 1.25, 95% CI 1.09–1.44, p = 0.002; Model 3: OR 1.22, 95%CI 1.06–1.41, p = 0.01). Subgroup analyses revealed that factors such as age, sex, sleep trouble, diabetes, hypertension, BMI, RIP, and race did not affect the association between blood lead levels and the risk of nocturia (P for interaction >0.05). Conclusions: This study reported the correlation between blood lead levels and nocturia. We found that compared to blood lead levels below 2 µg/dL, when lead levels reached or exceeded 2 µg/dL, the risk of nocturia occurrence increased by 22%. Clinical trial registration: This study is based on existing data from a public database and not from a specific clinical trial; hence, clinical registration information is not provided. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to investigate the association between diarrhea or constipation and urinary incontinence (UI) in adults. Methods: Data from the National Health and Nutrition Examination Survey for 2009–2010 was used to include 4686 adults aged 20 and over in the analysis. Stress urinary incontinence (SUI) and urgency urinary incontinence (UUI) were used as outcome variables, with diarrhea and constipation as exposure factors. We first compared the baseline characteristics of those with and without SUI, as well as those with and without UUI. The impact of diarrhea or constipation on SUI and UUI was assessed using multivariate logistic regression models. To ensure the stability of the results, subgroup and stratified analyses were conducted. Results: The prevalence rates of UUI and SUI were 22.49% and 23.39%, respectively. Adjusted multivariate logistic regression analysis revealed that the risk of UUI was increased by either diarrhea (OR 1.66, 95% CI 1.36–2.04) or constipation (OR 1.42, 95% CI 1.11–1.83). The risk of SUI was also elevated by either diarrhea (OR 1.36, 95% CI 1.11–1.67) or constipation (OR 1.32, 95% CI 1.06–1.63). Subgroup analysis revealed no significant differences in the interaction tests between constipation or diarrhea and UI. Conclusions: This study found that both constipation and diarrhea increase the risk of UUI and SUI. [ABSTRACT FROM AUTHOR]

Background: The relationship between waist circumference and nocturia has not been previously studied. This study investigated the association between waist circumference and the occurrence of nocturia in adults. Methods: We analyzed data from the National Health and Nutrition Examination Survey covering 2005–2020, encompassing 6287 adults aged ≥20. Nocturia was defined as the need to urinate two or more times during the night. First, we compared baseline characteristics between the nocturia and non‐nocturia groups. Subsequently, we used multivariate logistic regression analysis to investigate the relationship between waist circumference and nocturia prevalence. We also employed restricted cubic spline analysis to study the potential nonlinear correlation between waist circumference and the prevalence of nocturia. Recognizing the baseline data's heterogeneity based on nocturia prevalence, we conducted subgroup analyses according to age, sex, body mass index (BMI), and ethnicity. Results: Our findings indicated that females, individuals aged ≥50, citizens, Non‐Hispanic Black, those with lower education levels (high school or less), higher BMIs, lower family income‐to‐poverty ratios, higher waist circumference, hypertension, and diabetes were more likely to experience nocturia. Compared with individuals in the lowest waist circumference quartile (Q1), those in the higher quartiles (Q4) exhibited an increased risk of nocturia in Model 1 (Q4, OR:2.00, 95% CI:1.64, 2.45, p < 0.0001). These results remained consistent after adjusting for covariates in models 2 and 3. A restricted cubic spline analysis suggested a linear association between waist circumference and nocturia (P for nonlinearity = 0.066). Subgroup analyses based on age, sex, BMI, and ethnicity revealed no significant differences in the interaction tests between waist circumference and nocturia (P for interaction = 0.437, 0.331, 0.121, and 0.889, respectively), indicating that these baseline characteristics did not influence the association. Conclusions: Our findings indicated an association between increased waist circumference and a higher prevalence of nocturia. Knowledge of this association reinforces the importance of lifestyle modifications in maintaining a healthy waist circumference and informs public health strategies to address other potential risk factors for nocturia. [ABSTRACT FROM AUTHOR]

The study focused on the application value of the space compounding algorithm‐based colour Doppler ultrasound twinkling artefacts in predicting chemical components of urinary tract stones. Specifically, the minimum variance method was used to optimize the space‐compounding algorithm to improve the quality of colour Doppler ultrasound artefacts. Then, the urinary system stone model was built to quantitatively analyse the influence of stone components on colour Doppler twinkling artefacts. The results showed that no notable differences were noted in the twinkling artefact intensity (TAI), the width of twinkling artefact (TAW), and the length of twinkling artefact (TAL) between the oxalic acid monohydrate, hydroxyapatite, uric acid, and cystine stone models (p < 0.01). The area under the curve (AUC) of the TAI for the diagnosis of calcium‐free calculus models was 0.978, that of TAW was 0.9462, and that of TAL was 0.9315. The diagnostic sensitivity and specificity of TAI were 89% and 96%, respectively, the diagnostic sensitivity and specificity of TAW were 86% and 80%, respectively, and the diagnostic sensitivity and specificity of TAL were 78% and 97%, respectively. The ability of TAL (AUC of 0.953) to distinguish between hydroxyapatite stone model and cystine stone was better than TAI (AUC of 0.702) and TAW (AUC of 0.657) (p < 0.01); and TAL and TAW were positively correlated with TAI (R2 was 0.79 and 0.68, respectively, p < 0.01). In conclusion, the space compounding algorithm based on minimum variance method can improve the quality of colour Doppler ultrasound twinkling artefacts, and colour Doppler ultrasound twinkling artefacts can predict the chemical components of urinary stones, which can be used as a criterion for clinical diagnosis. [ABSTRACT FROM AUTHOR]