1. Association between triglyceride glucose body mass index and urinary incontinence: a cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) 2001 to 2018
- Author
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JiHang Li, Ruijie Xie, Hu Tian, Dong Wang, MingShen Mo, JianKun Yang, and WenBin Guo
- Subjects
Triglyceride glucose body mass index ,Urinary incontinence ,Insulin resistance ,Cross-sectional study ,NHANES ,Nutritional diseases. Deficiency diseases ,RC620-627 - Abstract
Abstract Background Urinary incontinence (UI) is a prevalent, health-threatening condition that causes isolation and psychological strain, leading to significant personal distress. The connection between the triglyceride glucose body mass index (TyG-BMI) and UI remains elusive. The purpose of the current research was to investigate any possible relationships between raised TyG-BMI levels and a higher likelihood of UI. Methods For a thorough examination, adults 20 years and older with UI were included in cross-sectional research using the data obtained from the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2018. Our investigation centred on three of the significant varieties of UI: Urgent Urinary Incontinence (UUI), Mixed Urinary Incontinence (MUI), and Stress Urinary Incontinence (SUI), employing weighted multivariate logistic regression models for an in-depth evaluation. The TyG-BMI, a possible biomarker, was arranged in increasing order among participants and then assessed with a trend test (P for trend). Moreover, this investigation delved into the non-linear relationships using advanced smoothed curve fitting techniques. Meticulous subgroup analyses were executed to verify the uniformity of the UI and TyG-BMI relationship across diverse demographic groups. Results A thorough investigation was conducted with 18,751 subjects to analyze the prevalence and types of UI, showing that 23.59% of individuals suffered from SUI, 19.42% from UUI, and 9.32% from MUI. Considering all possible confounding variables, Multivariate logistic regression analysis showed a substantial relationship between elevated TyG-BMI values and a greater likelihood across all UI categories. Specifically, stratifying the TyG-BMI into quartiles revealed a pronounced positive correlation in the top quartile relative to the bottom, reflected in increased odds ratios for SUI, UUI, and MUI (SUI: OR = 2.36, 95% CI 2.03–2.78, P
- Published
- 2024
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