Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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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 < 0.0001; UUI: OR = 1.86, 95% CI 1.65-2.09, P < 0.0001; MUI: OR = 2.07, 95% CI 1.71-2.51, P < 0.0001).
Conclusions: Among US adults, an association has been observed wherein increased TyG-BMI values correlate with a higher chance of UI. This suggests that TyG-BMI might be a helpful marker for identifying individuals at risk of UI, providing novel insights into its assessment and management.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11415990 | PMC |
http://dx.doi.org/10.1186/s12944-024-02306-7 | DOI Listing |