Association between estimated pulse wave velocity and gynecological cancer risk and mortality: Insights from NHANES 2003 to 2016

Estimated pulse wave velocity (ePWV) has been proposed as a potential substitute for carotid-femoral pulse wave velocity (cfPWV), serving as an indicator for assessing aortic stiffness. Arterial stiffness has emerged as a potential marker associated with adverse outcomes in various specific diseases, yet its relationship with mortality rates in the general adult population remains unstudied. This study aims to investigate the association between arterial stiffness and both all-cause and cardiovascular mortality among US adults. Data from 48,257 participants aged 20 and older in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 were analyzed. Mortality details were obtained from the National Death Index (NDI). Restricted cubic spline (RCS) functions were used to visualize the association between estimated pulse wave velocity (ePWV) and mortality risk. Weighted Cox proportional hazards models were employed to assess the independent correlation between ePWV and mortality risk. Time-dependent receiver operating characteristic (ROC) curve analysis was conducted to evaluate the predictive ability of ePWV for survival. Further subgroup analyses were performed to validate the robustness of the associations. Participants were stratified into higher (> 10.92) and lower (≤ 10.92) ePWV groups. During a median follow-up of 133.69 ± 94.42 months, 8029 (16.6%) deaths, including 2641 (5.5%) cardiovascular deaths, occurred among the 48,257 participants. The weighted Cox proportional hazards model showed that after comprehensive adjustment for covariates, individuals with higher ePWV had significantly increased risks of all-cause mortality (HR 2.67, 95% confidence interval [CI] 2.50–2.84, P < 0.001) and cardiovascular mortality (HR 2.75, 95%CI 2.46–3.07, P < 0.001). RCS regression analysis revealed a nonlinear association between ePWV, a marker of arterial stiffness, and all-cause mortality with an inflection point at 8.267 (P for nonlinear = 0.0001), while a positive linear correlation was observed with cardiovascular mortality (P for nonlinear = 0.889). This association was consistent across subgroups based on age, gender, race, body mass index, education level, marital status, smoking, alcohol consumption, diabetes, and hypertension, with significant interactions observed for all-cause mortality in the hypertension subgroup (P for interaction = 0.012) and for cardiovascular mortality in smoking (P for interaction = 0.032), diabetes (P for interaction < 0.001), and hypertension subgroups (P for interaction = 0.012). The time-dependent ROC curves indicated areas under the curve (AUCs) of 0.73, 0.80, and 0.79 for 1-year, 6-year, and 10-year survival rates, respectively, for all-cause mortality, and 0.85, 0.83, and 0.83 for cardiovascular mortality. Elevated ePWV is independently associated with increased cardiovascular mortality in US adults and exhibits a significant positive correlation with all-cause mortality in US adults beyond an ePWV threshold of 8.267.

BackgroundGynecologic cancers pose a significant threat to women’s health worldwide, with obesity and related metabolic dysfunction recognized as key risk factors. Traditional measures, such as body mass index (BMI), fail to adequately capture visceral fat, which plays a crucial role in tumorigenesis through metabolic and inflammatory pathways. This study aims to assess the association between the age-adjusted visceral adiposity index (AVAI) and the risk of gynecologic cancers using data from the National Health and Nutrition Examination Survey (NHANES).MethodsThis study analyzed a cross-sectional dataset from the NHANES [2007–2018], comprising 7,855 women, including 237 with gynecologic cancers (ovarian, endometrial, and cervical cancers) and 7,618 control participants without cancer. The AVAI was the main exposure variable. To control for potential confounders, such as age, race, educational level, the poverty-to-income ratio (PIR), smoking status, alcohol intake, hypertension, diabetes, and the BMI, multivariable logistic regression and generalized additive models were employed. The independent link between the AVAI and the risk of gynecologic cancers was examined. Additionally, subgroup analyses and restricted cubic spline functions were used to assess dose-response trends, while receiver operating characteristic (ROC) curves were generated to evaluate the discriminative performance of the AVAI.ResultsWomen with gynecologic cancers were older (P=0.02) and had higher waist circumference (WC), BMI, triglyceride (TG), and AVAI levels (P<0.001) than those in the control group. In the fully adjusted model I, each unit increase in the AVAI was associated with a 28.0% higher risk of gynecologic malignancies [odds ratio (OR) =1.280, 95% confidence interval (CI): 1.089–1.504, P=0.003]. Subgroup analysis showed a significant association with cervical cancer: each unit increase in AVAI resulting in a 30.9% higher risk in model I (P=0.02) and a 45.6% higher risk in model II (P=0.03), revealing a dose-response trend [Q2 (−8.7292 to −6.3966) vs. Q1 (<−8.7292): OR =2.085, P=0.007; Q3 (>−6.3966) vs. Q1: OR =2.974, P=0.02]. No statistically significant correlation was found between the AVAI and the risk of ovarian or endometrial cancers (P>0.05). ROC analysis showed that the area under the curve (AUC) of the AVAI for distinguishing women with and without gynecologic cancers was 0.807 (95% CI: 0.790–0.825, P<0.001).ConclusionsThe AVAI, a composite index that integrates visceral fat distribution and metabolic function, was shown for the first time to be significantly associated with the risk of gynecologic malignancies, particularly cervical cancer, for which it demonstrated strong discriminative value. The study shows the superiority of the AVAI over traditional BMI in metabolic-inflammatory risk stratification, offering a new target for early identification and targeted interventions in gynecologic cancers. Future prospective cohort studies need to be conducted to verify causality and explore metabolic regulation strategies targeting the AVAI to reduce the risk of cancers.

BackgroundLimited data on the correlation between estimated pulse wave velocity (ePWV) and chronic kidney disease (CKD) necessitate further investigation. This study aims to explore the association between ePWV and the prevalence of CKD.MethodsA cross-sectional study was conducted with 41,411 participants from the 1999–2020 National Health and Nutrition Examination Survey (NHANES). ePWV was calculated using an established equation from the Reference Values for Arterial Stiffness Collaboration, incorporating age and mean blood pressure. CKD prevalence was assessed as the primary outcome. Weighted logistic regression and linear models were applied for statistical analysis, with Restricted Cubic Splines (RCS) used to evaluate potential nonlinear associations. Subgroup analyses were conducted to assess variations and ensure the robustness of results.ResultsHigher ePWV was consistently associated with an increased prevalence of CKD. RCS analysis identified a significant positive nonlinear relationship. Subgroup analyses revealed sex-based and glucose metabolism abnormality-based differences, highlighting interactive correlations that provided further insights into the ePWV-CKD relationship.ConclusionThis study demonstrates a strong positive association between ePWV and CKD prevalence, underscoring the importance of monitoring arterial stiffness. The use of RCS and subgroup analyses enriched the findings and offered valuable directions for future research.

This study aimed to analyze the association between the Dietary Inflammatory Index (DII) and the risk of gynecological cancers using data collected from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2018. The data for this study were obtained from NHANES, conducted between 2011 and 2018, and included a total of 8,380 women. To examine the association between the Dietary Inflammatory Index and gynecological cancers, weighted multivariable logistic regression analyses were performed, using DII both as a continuous variable and as a categorical variable divided into tertiles. Subgroup analyses stratified by DII and gynecological cancer characteristics were conducted to further explore this association. Additionally, restricted cubic spline (RCS) analysis was applied to evaluate potential non-linear relationships between DII and gynecological cancer risk. Among the 8,380 women included in the analysis, the mean age was 47.02 (SD: 16.91) years, and 196 participants self-reported a diagnosis of gynecological cancer. In fully adjusted models, DII was significantly positively associated with the prevalence of gynecological cancer, whether analyzed as a continuous variable (OR = 1.15, 95% CI: 1.00-1.33, p = 0.046) or as a categorical variable (highest tertile compared to the lowest tertile: OR = 2.14, 95% CI: 1.14-4.04, p = 0.021, p for trend = 0.021). Restricted cubic spline analysis confirmed a linear relationship between DII and gynecological cancer risk (p for non-linear association = 0.1984). Subgroup analyses revealed a significant interaction effect with smoking status (p for interaction = 0.037). Our findings suggest that higher DII scores are positively associated with an increased risk of gynecological cancer. These results contribute to the existing literature and underscore the need for further validation through larger prospective cohort studies.

Background The present study systematically explores the correlation between the Prognostic Nutritional Index (PNI) and anemia, and further analysis of its association with all-cause mortality among populations affected by anemia. Methods Data were taken from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. We utilized multiple logistic regression models, Cox proportional hazards models, restricted cubic spline (RCS) analysis, and time-dependent receiver operating characteristic (ROC) analysis. As for the verification of the result robustness, subgroup and sensitivity analyses were implemented. Results A cohort of 28,511 participants was examined, of whom 2647 (9.28%) had anemia. An inverse relationship of PNI with anemia was detected in the fully adjusted model (OR = 0.82, 95%CI: 0.80–0.84). Cox regression showed that lower PNI levels were linked to higher all-cause mortality in people with anemia (HR = 0.91, 95%CI: 0.88–0.95). A non-linear correlation between PNI and mortality was detected through RCS analysis (P < 0.001). Significant interaction effects of PNI with mortality were observed across diabetes and BMI subgroups (P < 0.05). The predictive power of PNI for all-cause mortality among anemia individuals showed areas under the curve (AUC) values of 0.702, 0.806, and 0.813 for 3-, 5-, and 10-year predictions, respectively. Conclusion PNI demonstrates a negative association with anemia and a similar negative relationship with all-cause mortality in individuals with anemia. Future studies are warranted to substantiate these findings.

The prognosis of heart failure (HF) is closely linked to inflammation and nutritional status. The advanced lung cancer inflammation index (ALI) is a composite indicator consisting of several parameters used to assess inflammation and nutritional status. Our study aimed to investigate the prognostic value of ALI in HF patients. The data from Study 1, which included 1359 HF patients, were extracted from the National Health and Nutrition Examination Survey (NHANES) database spanning the years 1999 to 2018. Study 2 analysed data from patients with HF who underwent cardiac magnetic resonance imaging examinations from 2020 to 2023. Kaplan-Meier curve analysis, Cox proportional hazard model, time-dependent receiver operating characteristic (ROC) curve and restricted cubic spline (RCS) were used to evaluate the relationship between ALI and long-term prognosis of patients with HF in Study 1. Logistic regression analysis was used to evaluate the correlation between ALI and left ventricular reverse remodelling, and RCS was used to determine any dose-response relationship. Spearman correlation was used to evaluate the relationship between ALI and indicators of cardiac structural changes. Study 1 found that the average age of the patients was 68years [inter-quartile range (IQR) 58-76], the proportion of males was 54.3%, and there were 699 all-cause mortality and 293 cardiovascular mortality cases. After adjusted by multivariable Cox regression analysis, elevated ALI levels were significantly associated with increased risks of all-cause [hazard ratio (HR)=0.58, 95% confidence interval (CI)=0.42-0.79, P<0.001] and cardiovascular mortality (HR=0.61, 95% CI=0.38-0.97, P=0.036) in patients with HF. A linear negative correlation was observed between ALI and both all-cause (P=0.0011 and P<0.001, P for nonlinear=0.3993) and cardiovascular mortality (P=0.0011, P for nonlinear=0.5198). Time-dependent ROC curves showed the predictive value of ALI for all-cause mortality [area under the curve (AUC)=0.678 in 3years, AUC=0.674 in 5years and AUC=0.683 in 10years] and cardiovascular mortality (AUC=0.694 in 3years, AUC=0.685 in 5years and AUC=0.697 in 10years). Study 2 included 79 patients; the average age of the patients was 44years (IQR 35-55); and the proportion of males was 74.7%. Adjusted multivariable logistic regression analysis indicated that high ALI levels were associated with left ventricular reverse remodelling (LVRR) in patients with HF following discharge from the hospital [odds ratio (OR)=3.16, 95% CI=1.06-10.8, P=0.049]. Spearman analysis revealed a correlation between ALI and extracellular volume (ECV) (r=-0.25, P=0.023). ALI is associated with all-cause and cardiovascular mortality risk and structural changes in the heart in patients with HF.

This study aims to analyze the association between the weight-adjusted waist index (WWI) and the risk of gynecologic cancers, using data collected from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2016. We employed multiple logistic regression analysis to investigate the relationship between WWI and risk of gynecologic cancers. Subsequent subgroup analyses were performed on specific populations of interest. A restricted cubic spline model was used to explore potential non-linear relationships. Additionally, the effectiveness of WWI in predicting sarcopenia was assessed through Receiver Operating Characteristic (ROC) curve analysis. K-fold cross-validation was applied for model assessment. Among the 4,144 participants, 98 self-reported having gynecologic cancers. In the fully adjusted model, WWI was significantly associated with the prevalence of gynecologic cancers (OR = 1.38, 95% CI: 1.02-1.88, p = 0.0344). Our findings indicate a linear positive association between WWI and the risk of gynecologic cancers. Subgroup analysis revealed that WWI had the strongest association with cervical cancer (OR = 1.46, 95% CI: 0.97-2.18, p = 0.0354) and endometrial cancer (OR = 1.39, 95% CI: 0.81-2.39, p = 0.0142). No significant association was found between WWI and the risk of ovarian cancer (OR = 1.16, 95% CI: 0.48-2.72, p = 0.5359). Restricted cubic spline analysis confirmed a linear relationship between WWI and the risk of cervical, endometrial, and ovarian cancers. ROC curve analysis demonstrated that WWI had superior predictive capability for gynecologic cancers. Elevated levels of WWI were significantly associated with an increased risk of gynecologic cancers in American women, displaying a stronger association than other obesity markers. Therefore, WWI may serve as a distinct and valuable biomarker for assessing the risk of gynecologic cancers, particularly cervical and endometrial cancers.

Association between remnant cholesterol and arterial stiffness: Evidence from NHANES 1999-2018.

BackgroundThe remnant cholesterol inflammatory index (RCII) is a novel metric that combines remnant cholesterol and high-sensitivity C-reactive protein, reflecting the metabolic and inflammatory risk. This study investigates the association between RCII and long-term risks of all-cause and cause-specific mortality in middle-aged and elderly populations in the US and China.MethodWe analyzed data from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS), including 7,565 and 12,932 participants aged 45 years and older, respectively. The participants were categorized into quartiles based on natural log-transformed RCII (lnRCII) values. Kaplan–Meier survival analysis, Cox proportional hazards models, restricted cubic splines (RCS) and mediation analysis were used to examine the relationship between lnRCII and mortality outcomes, adjusting for potential covariates.ResultThe mean age of the participants was 59.90 ± 10.44 years (NHANES) and 58.64 ± 9.78 years (CHARLS), with 53.28% and 52.50% female, respectively. Kaplan–Meier survival analysis showed that higher lnRCII quartiles (≥ 0.79 in NHANES, ≥ -0.13 in CHARLS) were significantly associated with increased all-cause mortality risk (p < 0.001). Each standard deviation (SD) increase in lnRCII corresponded to a higher risk of all-cause mortality, and the hazard ratios (HRs) and 95% confidence interval (CI) were 1.29 (95% CI: 1.21–1.36) in NHANES and 1.26 (95% CI: 1.15–1.38) in CHARLS. In NHANES, lnRCII was also associated with elevated risks of cardiovascular mortality (HR = 1.21, 95% CI: 1.08–1.35) and cancer mortality (HR = 1.30, 95% CI: 1.09–1.55). RCS analysis indicated a J-shaped relationship between lnRCII and both all-cause and cardiovascular mortality, and a linear association with cancer mortality. Mediation analysis showed that systolic blood pressure and fasting plasma glucose partially mediated these associations. Subgroup analyses suggested a stronger association between lnRCII and all-cause mortality in middle-aged US participants (p for interaction = 0.010).ConclusionsElevated RCII levels are significantly associated with increased all-cause mortality risk middle-aged and elderly populations in both the US and China. In the US population, RCII is also associated with increased risks of cardiovascular and cancer mortality. By integrating metabolic and inflammatory risk factors, RCII may serve as a valuable tool for mortality risk stratification and clinical decision-making.

Identifying reliable prognostic indicators is essential for the appropriate management of non-alcoholic fatty liver disease (NAFLD). Red blood cell distribution width (RDW) has been established as an inflammatory marker associated with cardiovascular outcomes. This study aimed to evaluate the association between RDW and both cardiovascular and all-cause mortality in individuals with NAFLD. Data from 7,438 participants with NAFLD were analyzed, collected between 2005 and 2016 through the National Health and Nutrition Examination Survey (NHANES). Mortality data were retrieved from the National Death Index (NDI). Restricted cubic spline (RCS) analysis was used to illustrate the relationship between RDW and mortality risk, Weighted Cox proportional hazards models were used to assess the independent relationship between RDW and mortality risk. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive ability of RDW for survival outcomes. During a median follow-up period of 124 months, 1,269 deaths were recorded, including 335 from cardiovascular causes. RDW positively correlated with both cardiovascular and all-cause mortality according to the RCS analysis. Participants were categorized into quartiles based on RDW levels. Those in the highest RDW quartile (Q4) demonstrated a significantly higher risk of cardiovascular mortality (HR 3.61, 95% confidence interval [CI]:2.17-6.02, P=0.009) and all-cause mortality (HR 2.29, 95% CI:1.72-3.06, P < 0.0001), according to the weighted Cox hazards models. Additionally, the area under the curve (AUC) for all-cause mortality at 3, 5 and 10 years was, 0.69, 0.67, and 0.66, respectively. For cardiovascular mortality, the AUCs were 0.70, 0.68, and 0.68, respectively. Among patients with NAFLD, RDW was identified as an independent predictor of increased cardiovascular and all-cause mortality risk.

Association of neutrophil-to-lymphocyte ratio and risk of cardiovascular and all-cause mortality in hypertension patients

Cardiovascular diseases (CVD) and mortality remain significant public health challenges, especially among middle-aged and older adults. However, their relationship with Uric Acid to High-Density Lipoprotein Cholesterol Ratio (UHR) has not been extensively studied in the US population. This study aimed to examine these associations in adults aged ≥ 40 based on the National Health and Nutrition Examination Survey (NHANES) 1999–2018. 29,742 participants’ data in NHANES between 1999 and 2018 were retrospectively analyzed. Multivariable logistic regression, Cox proportional hazards models, restricted cubic spline (RCS) analyses, and subgroup analyses were used to assess the associations between UHR and various CVD outcomes. Among the participants, 4,505 (15.15%) reported a history of CVD. A positive association was observed between UHR and the risk of total CVD, including coronary heart disease, heart attack, heart failure, angina pectoris, and stroke (Pall < 0.05). UHR was associated with increased risks of all-cause mortality (HR = 1.02, 95% CI: 1.02–1.03) and CVD-specific mortality (HR = 1.03, 95% CI: 1.02–1.05). UHR had a linear dose-response relationship with CVD and a nonlinear relationship with all-cause mortality by RCS analyses. Subgroup analyses confirmed that these associations remained stable across different groups. The findings highlight UHR as a significant predictor of CVD risk and mortality in middle- and older-age adults. Given its strong association with adverse health outcomes, UHR can be a valuable indicator in facilitating the early identification of individuals at elevated cardiovascular risk.

Based on data from the National Health and Nutrition Examination Survey (NHANES), this work aimed to probe into the linkage between estimated pulse wave velocity (ePWV) and the risk and mortality of chronic kidney disease (CKD). Data from five cycles (2009-2018) of the NHANES database were analyzed, with ePWV as the independent variable and CKD as the dependent variable. Weighted logistic regression analysis was undertaken. First, a stratified analysis of unadjusted confounding variables was conducted, and the P-value of the interaction term after adjusting for all confounders was evaluated using the chi-square test. Subsequently, ePWV was stratified into quartiles, and regression models of ePWV and CKD were created with adjustments for different confounding factors. The association threshold between ePWV and CKD was studied using restricted cubic spline (RCS) and threshold effect analysis. Kaplan-Meier (K-M) curves were plotted to study the relationship between ePWV and all-cause mortality and mortality induced by cardiovascular disease (CVD) in CKD patients. The association between ePWV and mortality risk was assessed using multivariable-adjusted Cox regression and Fine-Gray competing risk models, with model predictive performance compared via Harrell's C-index. Triple sensitivity analyses were conducted to verify the robustness of the results. This study included a total of 22,438 participants. Stratified analyses demonstrated that elevated ePWV was significantly associated with an increased risk of CKD across all populations (P < 0.001). Interaction terms adjusted for all covariates indicated that gender, BMI, and T2D significantly influenced this association (P < 0.05). Elevated ePWV was consistently associated with a higher CKD risk in the unadjusted model (Crude), partially adjusted model (Model I), and fully adjusted model (Model II) (OR > 1, P < 0.05). RCS and threshold effect analyses revealed a J-shaped relationship between ePWV and CKD. When ePWV exceeded 6.31m/s, each increment in ePWV was significantly associated with an increased CKD risk (OR = 1.38, 95% CI 1.32-1.44, P < 0.001). K-M survival curves demonstrated that over time, CKD patients in the highest ePWV quartile had significantly higher all-cause and CVD mortality rates compared to those in the lowest quartile (P < 0.05). Multivariable-adjusted Cox regression showed that, compared to the Q1 group, the Q3 (OR = 2.53, 95% CI 1.55-4.15) and Q4 (OR = 4.12, 95% CI 2.38-7.13) groups had significantly elevated all-cause mortality risk (P < 0.001). The competing risk model further confirmed that Q4 was associated with a significantly higher CVD mortality risk than Q1 (OR = 2.71, 95% CI 1.24-5.95, P = 0.013). Harrell's C-index indicated that ePWV provided statistically significant incremental predictive value for all-cause mortality risk (Δ = + 0.02, P < 0.001). Triple sensitivity analyses consistently validated the robust association between ePWV and CKD (P < 0.001). The ePWV is an independent risk factor for CKD, exhibiting a non-linear relationship with CKD risk. Gender, BMI, and T2D have a substantial impact on this association. Furthermore, higher ePWV levels were associated with increased mortality risk in CKD patients. In the future, the research on how to apply ePWV more effectively in clinical practice to identify the risk of CKD should be advanced, especially for populations with ePWV > 6.68m/s.

Objective:This study aimed to evaluate the association of conicity index (C-index), a marker of abdominal obesity, with hearing impairment (HI) in US adults using data from the National Health and Nutrition Examination Survey (NHANES).Methods:We conducted a cross-sectional investigation using data from nine NHANES cycles spanning from 2001 to 2018. The C-index was used as the independent variable, whereas HI—defined as a pure-tone average hearing threshold exceeding 25 dB HL—was the outcome measure. Multivariable logistic regression models were used to assess the association between C-index and HI, adjusting for potential confounders including age, sex, race/ethnicity, hypertension, diabetes, total cholesterol, haemoglobin and blood urea nitrogen. Dose–response relationships were evaluated using trend tests (P for trend) and restricted cubic spline (RCS) analysis. Subgroup analyses were performed to assess potential interaction effects.Results:A total of 7394 adults aged 20–69 were included. Higher C-index values were significantly associated with an increased prevalence of HI. In the fully adjusted model, each unit increase in C-index was associated with 7.35-fold higher odds of HI (95% CI: 3.03–17.82, P < 0.01). When stratified into tertiles, individuals in the highest tertile had a 57% higher likelihood of HI compared to the lowest tertile (Odds Ratio = 1.57, 95% Confidence Interval: 1.14–2.18, P < 0.01). RCS analysis indicated a significant non-linear association (P for non-linearity < 0.05) with an inflection point at a C-index of 1.17. Subgroup analysis revealed significant interaction effects of C-index with gender, diabetes and hypertension (P for interaction < 0.05) but not with age (P > 0.05).Conclusion:Higher C-index values are independently associated with greater odds of HI. Given the rising burden of obesity and its metabolic consequences, the C-index may serve as a practical tool for HI risk assessment, especially in populations with cardiometabolic risk factors.

BackgroundEstimated pulse wave velocity (ePWV) has been proposed as a potential approach to estimate carotid-femoral pulse wave velocity. However, the potential of ePWV in predicting all-cause mortality (ACM) and cardiovascular disease mortality (CVM) in the general population is unclear.MethodsWe conducted a prospective cohort study using the data of 33,930 adults (age ≥ 20 years) from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014 until the end of December 2019. The study outcomes included ACM and CVM. Survey-weighted Cox proportional hazards models were used to assess hazard ratios (HRs) and 95% confidence intervals (CIs) to determine the association between ePWV and ACM and CVM. To further investigate whether ePWV was superior to traditional risk factors in predicting ACM and CVM, comparisons between ePWV and the Framingham Risk Score (FRS) and Pooled Cohort Equations (PCE) models were performed. Integrated Discriminant Improvement (IDI) and Net Reclassification Improvement (NRI) were employed to analyze differences in predictive ability between models.ResultsThe weighted mean age of the 33,930 adults included was 45.2 years, and 50.28% of all participants were men. In the fully adjusted Cox regression model, each 1 m/s increase in ePWV was associated with 50% and 49% increases in the risk of ACM (HR 1.50; 95% CI, 1.45–1.54) and CVM (HR 1.49; 95% CI, 1.41–1.57), respectively. After adjusting for FRS, each 1 m/s increase in ePWV was still associated with 29% (HR 1.29; 95% CI, 1.24–1.34) and 34% (HR 1.34; 95% CI, 1.23–1.45) increases in the risk of ACM and CVM, respectively. The area under the curve (AUC) predicted by ePWV for 10-year ACM and CVM were 0.822 and 0.835, respectively. Compared with the FRS model, the ePWV model improved the predictive value of ACM and CVM by 5.1% and 3.8%, respectively, with no further improvement in event classification. In comparison with the PCE model, the ePWV model’s ability to predict 10-year ACM and CVM was improved by 5.1% and 3.5%, and event classification improvement was improved by 34.5% and 37.4%.ConclusionsIn the U.S. adults, ePWV is an independent risk factor for ACM and CVM and is independent of traditional risk factors. In the general population aged 20 to 85 years, ePWV has a robust predictive value for the risk of ACM and CVM, superior to the FRS and PCE models. The predictive power of ePWV likely originates from the traditional risk factors incorporated into its calculation, rather than from an indirect association with measured pulse wave velocity.