Project description:BackgroundCardiometabolic index (CMI) is a comprehensive clinical parameter which integrates overweight and abnormal lipid metabolism. However, its relationship with all-cause, cardiovascular disease (CVD), and cancer mortality is still obscure. Thus, a large-scale cohort study was conducted to illustrate the causal relation between CMI and CVD, cancer, and all-cause mortality among the common American population.MethodsOur research was performed on the basis of National Health and Nutrition Examination Survey (NHANES) database, involving 40,275 participants ranging from 1999 to 2018. The formula of CMI is [waist circumference (cm) / height (cm)] × [triglyceride (mg/dL) / high-density lipoprotein cholesterol (mg/dL)]. Outcome variables consisted of CVD, cancer, and all-cause mortality, which were identified by the International Classification of Diseases (ICD)-10. The correlation between CMI and mortality outcomes was analyzed utilizing the Kaplan-Meier survival modeling, univariate/multivariate Cox regression analysis, smooth curve fitting analysis, threshold effect analysis, and subgroup analysis. Stratification factors for subgroups included age, race/ethnicity, sex, smoking behavior, drinking behavior, BMI, hypertension, and diabetes.ResultsThe baseline characteristics table includes 4,569 all-cause-induced death cases, 1,113 CVD-induced death cases, and 1,066 cancer-induced death cases. Without adjustment for potential covariates, significantly positive causal correlation existed between CMI and all-cause mortality (HR = 1.03, 95% CI 1.02,1.04, P-value<0.05), CVD mortality (HR = 1.04, 95% CI 1.03, 1.05, P-value<0.05) and cancer mortality(HR = 1.03, 95% CI 1.02, 1.05, P-value<0.05); whereas, after confounding factors were completely adjusted, the relationship lost statistical significance in CMI subgroups (P for trend>0.05). Subgroup analysis found no specific subgroups. Under a fully adjusted model, a threshold effect analysis was performed combined with smooth curve fitting, and the findings suggested an L-shaped nonlinear association within CMI and all-cause mortality (the Inflection point was 0.98); in particular, when the baseline CMI was below 0.98, there existed a negative correlation with all-cause mortality with significance (HR 0.59, 95% CI 0.43, 0.82, P-value<0.05). A nonlinear relation was observed between CMI and CVD mortality. Whereas, the correlation between CMI and cancer mortality was linear.ConclusionsAmong the general American population, baseline CMI levels exhibited an L-shaped nonlinear relationship with all-cause mortality, and the threshold value was 0.98. What's more, CMI may become an effective indicator for CVD, cancer, and all-cause mortality prediction. Further investigation is essential to confirm our findings.

Project description:ObjectiveTo investigate associations between visceral adiposity index (VAI) and cardiovascular and cerebrovascular diseases (CCDs) in the American population from 1999 to 2018.MethodsData from the National Health and Nutrition Examination Survey (1998-2018) were analyzed in this study. Specifically, VAI scores were calculated using sex-specific equations that incorporate body mass index, waist circumference (WC), high-density lipoprotein (HDL), triglycerides (TG), and cholesterol. Weighted logistic regression analysis was conducted to assess the relationship between VAI tertile and increased risk of CCDs. Restricted cubic splines were used to evaluate the non-linear relationship between VAI and CCDs, such as heart failure, angina, heart attack, stroke, hypertension, and coronary heart disease. Sensitivity analysis was conducted, using VAI quartiles as independent variables.ResultsA total of 22,622 subjects aged over 20 years were included. In the fully adjusted model after controlling for covariates, the third VAI tertile was more strongly associated with CCDs than the first VAI tertile, with odds ratio (OR) and 95% confidence interval (95% CI) values for angina of 2.86, 1.68-4.85; heart attack, 1.75, 1.14-2.69; stroke, 2.01, 1.23-3.26; hypertension, 2.28, 1.86-2.78; and coronary heart disease, 1.78, 1.32-2.41; but there was no significant association with heart failure (p > 0.05). Restricted cubic splines revealed parabolic relationships between VAI score and angina (p for non-linear = 0.03), coronary heart disease (p for non-linear = 0.01), and hypertension (p for non-linear < 0.001). Sensitivity analysis indicated that the fourth VAI quartile was more strongly associated with an increased risk of angina (OR = 2.92, 95% CI, 1.49-5.69), hypertension (OR = 2.37, 95% CI, 1.90-2.97), heart attack (OR = 1.77, 95% CI, 1.09-2.88), and coronary heart disease (OR = 1.89, 95% CI, 1.24-2.86) than the first VAI quartile. VAI had superior predictive power for prevalent CCDs than other independent indicators (p < 0.05).ConclusionVisceral adiposity index score is positively correlated with angina, heart attack, stroke, hypertension, and coronary heart disease, but not heart failure, and the relationships between VAI score and angina, hypertension, and coronary heart disease are non-linear.

Project description:BackgroundThe relationship between the triglyceride-glucose (TyG) index and its derived index, the triglyceride glucose-waist height ratio (TyG-WHtR), with mortality and cardiovascular diseases (CVDs) in patients with non-alcoholic fatty liver disease (NAFLD) remains unclear.MethodsThis study enrolled 6627 adults aged 18 and above diagnosed NAFLD from the National Health and Nutrition Examination Survey (NHANES, 1999-2018). Binary weighted logistic regression analyses, cox proportional hazards model and restricted cubic spline (RCS) were used to analyze the relationship between TyG and TyG-WHtR with all-cause mortality, CVD mortality and CVDs. Mediation analysis explored the mediating role of glycohemoglobin, insulin and hypertension in the above relationships. Meanwhile, the incremental predictive value of the TyG index and TyG-WHtR was further assessed.ResultsExcept for no significant association between the TyG index and both all-cause mortality and chronic heart failure (CHF), both TyG and TyG-WHtR exhibited significant positive correlations or trends of positive correlation with all-cause mortality, CVD mortality, total-CVD, CHF, coronary heart disease (CHD) and angina pectoris. For all-cause mortality, CVD mortality and CHF, TyG-WHtR was a better predictor than TyG (TyG-WHtR: HR 1.31, 95%CI 1.03-1.66; HR 2.22, 95%CI 1.42-3.47; OR 3.99, 95%CI 1.79-8.93). In contrast, TyG index demonstrated a stronger association with total-CVD, CHD and angina pectoris (TyG index: OR 2.00, 95%CI 1.26-3.18; OR 1.85, 95%CI 1.19-2.91; OR 2.93, 95%CI 1.23-7.00). RCS analysis showed that after adjusting for covariates, most of the aforementioned relationships were linear(P overall < 0.0001, P-nonlinear > 0.05), while the associations of the TyG index and TyG-WHtR with all-cause mortality and CHF were non-linear(P overall < 0.0001, P nonlinear < 0.05). The addition of the TyG index and TyG-WHtR to the basic model for outcomes improved the C-statistics, net reclassification improvement value, and integrated discrimination improvement value.ConclusionsThe predictive value of TyG or TyG-WHtR for all-cause mortality and cardiovascular risk in NAFLD patients was significant. The TyG index and TyG-WHtR might be valid predictors of cardiovascular outcomes of patients with NAFLD.

Project description:BackgroundOsteoarthritis (OA) is the most prevalent form of arthritis worldwide. Inflammation and nutrition status play crucial roles in the development and progression of OA. The advanced lung cancer inflammation index (ALI) serves as a composite indicator for evaluating inflammation and nutritional status, while the systemic immune inflammation index (SII) is a novel marker for assessing immune-related inflammation. The study aimed to investigate the associations of the ALI and SII with all-cause and cardiovascular mortality among US adults with OA.MethodsA total of 2,602 individuals aged 20 years and above with OA were included in the study from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. Participants were categorized into higher or lower ALI and SII groups using cut-off values determined by the maximally selected rank statistics method. The Kaplan-Meier analysis, Cox proportional hazards models, and Fine Gray competing risk regression models were employed to assess the associations between the ALI/SII and mortality in OA patients. Additionally, stratified and subgroup analyses were conducted to enhance the robustness of the findings. Furthermore, time-dependent receiver operating characteristic (ROC) analysis was used to evaluate the predictive capacity of ALI and SII for mortality.ResultsHigher SII levels were associated with a 2-fold increase in the risk of all-cause mortality (HR: 2.00, 95% CI: 1.59-2.52, p < 0.001), whereas individuals with higher ALI in the OA group exhibited a significantly reduced risk of all-cause mortality (HR: 0.49, 95% CI: 0.39-0.60, p < 0.001). Notably, in Model 3, individuals with higher ALI demonstrated a substantially lower risk of cardiovascular mortality (HR: 0.60, 95% CI: 0.44-0.82, p < 0.001). Conversely, in fully adjusted models, those with higher SII experienced a significantly higher risk (HR: 1.83, 95% CI: 1.29-2.60, p < 0.001). The RCS analysis revealed a J-shaped non-linear relationship between SII levels and all-cause mortality (p overall < 0.001; p non-linear < 0.001), and an L-shaped non-linear association between ALI levels and all-cause mortality (p overall < 0.001; p non-linear = 0.002). The time-dependent ROC curves illustrated that ALI and SII displayed a reasonably good and consistent predictive performance for both short- and long-term mortality in OA patients.ConclusionsLower ALI and higher SII values were correlated with increased risks of all-cause and cardiovascular mortality among US adults with OA.

Project description:BackgroundChronic inflammation is closely linked to Chronic Obstructive Pulmonary Disease (COPD); however, the impact of the Dietaryq Inflammatory Index (DII) on mortality among COPD patients remains uncertain.ObjectiveTo assess the correlation between the DII and all-cause mortality in COPD patients using data from the National Health and Nutrition Examination Survey (NHANES).MethodsWe conducted a retrospective cohort study on 1,820 COPD patients from the NHANES dataset (1999-2018). The influence of DII on mortality was evaluated using multivariate Cox regression, smoothing spline fitting, and threshold effect analysis. Additionally, Kaplan-Meier survival analysis was performed to compare survival curves among different DII groups. Subgroup analyses and E-values identified sensitive cohorts and assessed unmeasured confounding.ResultsOver an average follow-up of 91 months, multivariate Cox regression models revealed a significant positive correlation between DII scores and mortality risk, with each unit increase in DII associated with a 10% higher risk of death (HR: 1.10, 95% CI: 1.03-1.16; P = 0.002). Among the DII tertiles, individuals in the second tertile (T2: 1.23-2.94) experienced a 67% increase in mortality risk compared to those in the lowest tertile (T1: -5.28-1.23) (HR: 1.67, 95% CI: 1.26-2.21; p < 0.001). The third tertile (T3) did not show a statistically significant increase in mortality risk (HR: 1.30, 95% CI: 0.98-1.72; p=0.074). A restricted cubic spline analysis indicated a significant nonlinear association between DII and all-cause mortality (p = 0.021). Threshold effect analysis further revealed that below a DII of 2.19, there was a significant increase in all-cause mortality risk (HR = 1.19, 95% CI: 1.07-1.33; p = 0.002), while at or above this threshold, the risk increase was not statistically significant (HR=0.89, 95% CI: 0.68-1.15; p = 0.380). Kaplan-Meier analysis revealed significant differences in survival curves among DII tertiles (p < 0.001), with the lowest DII tertile showing the highest survival probability. Both subgroup and sensitivity analyses confirmed the robustness of these findings.ConclusionDII is positively correlated with mortality risk in COPD patients, showing nonlinear characteristics and threshold effects, underscoring its prognostic value.

Project description:BackgroundThe correlation between the triglyceride-glucose (TyG) index and mortality in the general population remains controversial, with inconsistent conclusions emerging from different studies.ObjectiveThis study aims to investigate whether there is an association between the TyG index and mortality in the general population in the United States, and to explore whether a new index combining the TyG index with systemic inflammation indicators can better predict all-cause and cardiovascular mortality risks in the general population than using the TyG index alone.MethodsCalculate the systemic inflammation indicators and TyG index for each participant based on their complete blood count, as well as their triglyceride and glucose levels in a fasting state. TyG-inflammation indices were obtained by multiplying the TyG index with systemic inflammation indicators (TyG-NLR, TyG-MLR, TyG-lgPLR, TyG-lgSII, and TyG-SIRI). Based on the weighted Cox proportional hazards model, assess whether the TyG and TyG-Inflammation indices are associated with mortality risk in the general population. Restricted cubic splines (RCS) are used to clarify the dose-response relationship between the TyG and TyG-Inflammation indices and mortality, and to visualize the results. Time-dependent receiver operating characteristic (ROC) curves are used to evaluate the accuracy of the TyG and TyG-Inflammation indices in predicting adverse outcomes.ResultsThis study included 17,118 participants. Over a median follow-up period of 125 months, 2595 patients died. The TyG index was not found to be related to mortality after adjusting for potentially confounding factors. However, the TyG-inflammation indices in the highest quartile (Q4), except for TyG-lgPLR, were significantly associated with both all-cause and cardiovascular mortality, compared to those in the lowest quartile (Q1). Among them, TyG-MLR and TyG-lgSII showed the strongest correlations with all-cause mortality and cardiovascular mortality. Specifically, compared to their respective lowest quartiles (Q1), participants in the highest quartile (Q4) of TyG-MLR had a 48% increased risk of all-cause mortality (95% CI: 1.23-1.77, P for trend < 0.0001), while participants in the highest quartile (Q4) of TyG-lgSII had a 92% increased risk of cardiovascular mortality (95% CI: 1.31-2.81, P for trend < 0.001). Time-dependent ROC curve analysis showed that the TyG-MLR had the highest accuracy in predicting long-term mortality outcomes.ConclusionsThe TyG-Inflammation indices constructed based on TyG and systemic inflammation indicators are closely related to mortality in the general population and can better predict the risk of adverse outcomes. However, no association between TyG and mortality in the general population was found.

Project description:BackgroundCardiovascular disease (CVD) is one of the leading global causes of death, and serum iron (SI) levels may be associated with the mortality of CVD. However, there is still a knowledge gap regarding the relationship between SI and mortality in the CVD population.MethodsAn analysis was conducted utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. In our study, SI was used as the independent variable, and the mortality of the CVD patients was considered as the outcome. Kaplan-Meier curves, multivariable Cox proportional hazards model, and restricted cubic spline were employed to examine the association between SI and all-cause mortality and cardiovascular mortality in CVD patients. Subgroup analysis was also carried out based on age, sex, weight, hypertension, Type 2 diabetes mellitus, and smoking status.ResultsA retrospective cohort study design was utilized, incorporating data from 1,903 CVD patients with an average age of 64.29 years. Kaplan-Meier survival analysis demonstrated significant differences in all-cause mortality and cardiovascular mortality among the CVD patients based on quartiles of SI. Following multivariable adjustment, lower SI was associated with an increased risk of all-cause and cardiovascular mortality in CVD patients. The highest quartile of SI exhibited a 43% reduction in all-cause mortality (HR = 0.57, 95% CI: 0.45-0.72) and a 74% reduction in cardiovascular mortality (HR = 0.26, 95% CI: 0.16-0.43) when compared to the lowest quartile. Restricted cubic spline showed a nonlinear relationship between SI and all-cause mortality and a linear relationship between SI and cardiovascular mortality. Additionally, the inverse relationship between SI levels and outcomes in the CVD patients remained consistent in subgroup analysis.ConclusionHigher SI is associated with a decreased risk of all-cause and cardiovascular mortality in CVD patients. Our results emphasize the importance of iron supplementation for this particular group.

Dataset Information

Relationship between advanced lung cancer inflammation index and long-term all-cause, cardiovascular, and cancer mortality among type 2 diabetes mellitus patients: NHANES, 1999–2018

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