Atherogenic Index of Plasma mediates the association between Life’s Crucial 9 with overactive bladder: a secondary data analysis from NHANES

Frontiers in Endocrinology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 28, 2025

Background Some studies suggest a potential link between cardiovascular health, lipid, and overactive bladder (OAB). Life’s Crucial 9 (LC9) is recently developed method for assessing while the Atherogenic Index of Plasma (AIP) represents novel marker atherosclerotic lipid profiles. However, relationship role in unclear. This study investigates evaluates whether influences this association. Methods conducted cross-sectional analysis 25,628 U.S. participants NHANES database from 2005-2018. Firstly, we used multivariate logistic regression to investigate bladder. Subsequently, subgroup restricted cubic splines (RCS) were further verify their relationship. Additionally, mediation was explore levels association Results A total included study, among whom 5,150 reported events. After using adjust age, sex, race, marital status, education level, poverty-to-income ratio (PIR), smoking, alcohol consumption, hypertension, diabetes, hypercholesterolemia, 10-unit increase associated with 28% reduction incidence (OR = 0.72, 95% CI: 0.69-0.76), 1-unit 7% 1.07, 1.01-1.14). Similar results obtained when categorized into tertiles, significant trend (P < 0.05). Restricted spline revealed linear negative correlation incidence. Mediation indicated that 6.49% mediated by 0.014). Conclusion found bladder, partially mediating These findings highlight health underscoring reducing incidence, possibly through its effects on lowering levels.

Language: Английский

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Association of atherogenic index of plasma trajectory with the incidence of cardiovascular disease over a 12-year follow-up: findings from the ELSA cohort study

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: March 19, 2025

Atherogenic index of plasma (AIP) at baseline has been associated with increased morbidity and mortality from cardiovascular disease (CVD). However, the relationship between long-term AIP trajectories CVD remains unclear. Therefore, this study aimed to investigate associations incidence in English population. The data analysis was based on Longitudinal Study Aging (ELSA) 2004 2017. population consisted individuals aged 50 years older England. calculated as log10 (triglycerides/high-density lipoprotein cholesterol). Group-based trajectory model (GBTM) applied identify Wave 2 8 over a 12-year follow-up. Cox proportional hazard models were then used analyze different groups CVD. A total 3976 participants completed more than two measurements enrolled ELSA cohort. divided into three [low-stable group (n = 1146), moderate-stable 2110), high-stable 720)] using GBTM model. After adjusting for potential confounders, indicated an risk developing incident compared those low-stable [Hazard Ratio (HR) 1.33; 95% Confidence Interval (CI) 1.02-1.74, P 0.033]. no differences (HR 1.20, 95%CI 0.98-1.48, 0.082) observed group. Subgroup similar results under 63 old high alcohol consumption. sustainable level may contribute can help who deserve primitive preventive therapeutic approaches.

Language: Английский

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Association between triglyceride glucose-body mass index and the trajectory of cardio-renal-metabolic multimorbidity: insights from multi-state modelling

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: March 21, 2025

Although some studies have examined the association between triglyceride glucose-body mass index (TyG-BMI) and cardiovascular outcomes in cardio-renal-metabolic (CRM) background, none explored its role progression of CRM multimorbidity. In addition, prior research is limited by small sample sizes a failure to account for competitive effects other diseases. this study, data obtained from large-scale, prospective UK Biobank cohort were used. multimorbidity was defined as new-onset ischemic heart disease, type 2 diabetes mellitus, or chronic kidney disease during follow-up. Multivariable Cox regression used analyse independent TyG-BMI each (first, double, triple diseases). The C-statistic calculated model, restricted cubic spline applied assess dose–response relationship. A multi-state model investigate trajectory (from baseline [without disease] first double disease), with disease-specific analyses. This study included 349,974 participants, mean age 56.05 (standard deviation [SD], 8.08), 55.93% whom female. Over median follow-up approximately 14 years, 56,659 (16.19%) participants without developed at least one including 8451 (14.92%) who progressed 789 (9.34%) further disease. crude SD increase associated 47% higher risk 72% 95% C-statistics 0.625, 0.694, 0.764, respectively. Multi-state analysis showed 32% increased new 24% 23% those significantly onset all individual diseases (except stroke) transition Significant interactions also observed, but remained across subgroups. Sensitivity analyses, varying time intervals entering states an expanded definition (including atrial fibrillation, failure, peripheral vascular obesity, dyslipidaemia), confirmed these findings. remarkably influences Incorporating it into prevention management could important public health implications.

Language: Английский

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Association between cumulative average triglyceride glucose-body mass index and the risk of CKD onset

Frontiers in Endocrinology, Journal Year: 2025, Volume and Issue: 16

Published: March 31, 2025

Background Chronic kidney disease (CKD) has become a significant global public health challenge, which was reported to be highly correlated with the triglyceride glucose-body mass index (TyG-BMI). Nevertheless, literature exploring association between changes in TyG-BMI and CKD incidence is scant, most studies focusing on individual values of TyG-BMI. We aimed investigate whether cumulative average were associated incidence. Methods Data our study obtained from China Health Retirement Longitudinal Study (CHARLS), an ongoing nationally representative prospective cohort study. The exposure 2011 2015. calculated by formula ln [TG (mg/dl) × FBG (mg/dl)/2] BMI (kg/m 2 ), as follows: (TyG-BMI + 2015 )/2. Logistic regressions used determine different quartiles Meanwhile, restricted cubic spline applied examine potential nonlinear In addition, subgroup analysis test robustness results. Results Of 6117 participants (mean [SD] age at baseline, 58.64 [8.61] years), 2793 (45.7%) men. During 4 years follow-up, 470 (7.7%) incident cases identified. After adjusting for confounders, compared lowest quartile TyG-BMI, 3rd 4th had higher risk onset. ORs 95%CIs [1.509(1.147, 1.990)] [1.452(1.085, 1.948)] respectively. showed liner ( p -nonlinear = 0.139). Conclusions independently middle-aged older adults. Monitoring long-term may assist early identification individuals high CKD.

Language: Английский

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hs-CRP/HDL-C can predict the risk of all cause mortality in cardiovascular-kidney-metabolic syndrome stage 1-4 patients

Frontiers in Endocrinology, Journal Year: 2025, Volume and Issue: 16

Published: April 10, 2025

Background The precise function of the hs-CRP/HDL-C ratio in forecasting long-term mortality risk patients with stages 1-4 Cardiovascular-Kidney-Metabolic (CKM) syndrome remains inadequately delineated. This study investigates potential correlation between and individuals CKM 1-4. Methods prospective cohort utilises data from China Health Retirement Longitudinal Study (CHARLS) project, encompassing 6,719 people who satisfied stringent criteria. We developed three Cox proportional hazards regression models to investigate relationship employed Restricted Cubic Spline (RCS) curves for analysis identify any nonlinear correlations. Furthermore, we performed Receiver Operating Characteristic (ROC) curve evaluate predictive performance appropriate cut-off value. To enhance research findings, conducted a stratified influence various sociodemographic factors on this association. Results In 1-4, 10-year incidence all-cause was 14.1%. Upon controlling additional confounding variables, outcomes model distinctly demonstrated statistically significant linear positive association patients. For each quartile increase ratio, probability poor (i.e., mortality) escalated by 15% (Hazard Ratio, HR = 1.15, 95% Confidence Interval, CI: 1.09–1.22, p-value < 0.001). Moreover, integration into baseline prediction model, all pertinent thoroughly adjusted, markedly enhanced model’s capacity, facilitating more assessment Conclusion identified 1 4 syndrome. remarkable discovery not only offers crucial reference enhancing early individualised treatment options but also greatly aids identification prognoses, hence presenting novel perspective improving clinical management pathways these individuals.

Language: Английский

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Estimated glucose disposal rate outperforms other insulin resistance surrogates in predicting incident cardiovascular diseases in cardiovascular-kidney-metabolic syndrome stages 0–3 and the development of a machine learning prediction model: a nationwide prospective cohort study

Cardiovascular Diabetology, Journal Year: 2025, Volume and Issue: 24(1)

Published: April 16, 2025

Background The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting increasing importance complex interplay between metabolic, renal, and cardiovascular diseases (CVD). While substantial evidence supports a correlation estimated glucose disposal rate (eGDR) CVD events, its predictive value compared with other insulin resistance (IR) indices, such as triglyceride–glucose (TyG) index, TyG-waist circumference, TyG-body mass TyG-waist-to-height ratio, triglyceride-to-high density lipoprotein cholesterol metabolic score for resistance, remains unclear. Methods This prospective cohort study utilized data from China Health Retirement Longitudinal Study (CHARLS). individuals were categorized into four subgroups based on quartiles eGDR. associations eGDR incident evaluated using multivariate logistic regression analyses restricted cubic spline. Seven machine learning models to assess index events. To model’s performance, we applied receiver operating characteristic (ROC) precision-recall (PR) curves, calibration decision curve analysis. Results A total 4,950 participants (mean age: 73.46 ± 9.93 years), including 50.4% females, enrolled in study. During follow-up 2011 2018, 697 (14.1%) developed CVD, 486 (9.8%) heart disease 263 (5.3%) stroke. outperformed six IR indices predicting demonstrating significant linear relationship all outcomes. Each 1-unit increase was associated 14%, 19% lower risk disease, stroke, respectively, fully adjusted model. incorporation significantly improved prediction performance area under ROC PR curves equal or exceeding 0.90 both training testing sets. Conclusions outperforms stroke CKM syndrome stages 0–3. Its enhances stratification may aid early identification high-risk this population. Further studies are needed validate these findings external cohorts. Graphical abstract

Language: Английский

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