Metabolic Syndrome and Obesity-Related Indices Are Associated with Rapid Renal Function Decline in a Large Taiwanese Population Follow-Up Study

Association between cardiac metabolic index and diabetic kidney disease: a cross-sectional study of NHANES 1999-2018

BACKGROUND

The Cardiac Metabolic Index (CMI) is a comprehensive metabolic indicator, but studies on its relationship with Diabetic Kidney Disease (DKD) are limited. We aim to explore the association between CMI and DKD.

METHODS

We obtained participant-related data from the National Health and Nutrition Examination Survey (NHANES), including complete information on DKD, CMI, and other covariates. We employed weighted multivariable logistic regression models, restricted cubic spline (RCS) regression analysis, subgroup analyses, and interaction tests to explore the relationship between CMI and DKD. Additionally, we utilized receiver operating characteristic (ROC) curves to compare the performance of CMI in identifying DKD relative to a body shape index (ABSI), body roundness index (BRI), visceral adiposity index (VAI), and lipid accumulation product (LAP) indices.

RESULTS

According to the logistic regression analysis, a positive correlation between CMI and DKD was observed among the 2371 participants included in the study (OR: 1.40, 95% CI: 1.19-1.66). RCS analysis indicated that this relationship is nonlinear. When CMI was converted from a continuous variable to quartiles, the prevalence of DKD in the highest quartile group showed a significant 84% increase compared to the lowest quartile group (OR: 1.84, 95% CI: 1.24-2.72). The area under the ROC curve of CMI for identifying DKD was 0.67, outperforming other indices. The results of subgroup analyses and interaction tests were stable.

CONCLUSION

Elevated CMI is associated with an increased risk of DKD and can serve as a low-cost screening tool, allowing physicians to potentially identify high-risk diabetic patients early and implement timely interventions to slow the progression of DKD.

Development and validation of a nomogram for arthritis: a cross-sectional study based on the NHANES

Previous epidemiological studies have associated various body-related indicators with arthritis; however, the results have been inconclusive. Therefore, this research aimed to develop and validate a nomogram model for predicting the risk of arthritis using easily available indicators and to assess the model's predictive performance. Cross-sectional data were collected from 3660 participants in the 2021-2023 National Health and Nutrition Examination Survey. The research conducted variable selection and model development using the Least Absolute Shrinkage and Selection Operator regression model and multivariate logistic regression analysis, and the performance of the nomogram was validated. The nomogram model incorporated nine independent predictors: age, sex, family poverty-income ratio, race, diabetes status, vitamin D level, systemic immunity-inflammation index, and waist-to-height ratio. After validation, it has been proven that the nomogram model has good performance. The nomogram model developed in this study effectively predicts the risk probability of arthritis in the general population of the United States. All variables included in this nomogram can be easily obtained from the population.

Obesity-related indices are associated with self-reported infertility in women: findings from the National Health and Nutrition Examination Survey

OBJECTIVE

Obesity can contribute to infertility, but the exact relationship between infertility risk and obesity-related measurements like waist-to-height ratio (WHtR), body roundness index (BRI), conicity index (CoI), and A body shape index (ABSI) in women is uncertain. We investigated the association between these indices and female infertility.

METHODS

In this cross-sectional study, we used National Health and Nutrition Examination Survey data (2013-2018). We used weighted multivariable logistic regression analysis, receiver operating characteristic (ROC) curves, and subgroup analysis, as well as propensity score matching.

RESULTS

Among 3373 participants, 344 (10.2%) reported infertility. A significant link between higher infertility risk and increased WHtR, BRI, CoI, ABSI, and body mass index (BMI) was found. Multivariable logistic regression analysis showed WHtR (odds ratio [OR] = 1.27, 95% confidence interval [CI]: 1.14-1.42), BRI (OR = 1.09, 95% CI: 1.05-1.14), CoI (OR = 1.36, 95% CI: 1.18-1.56), ABSI (OR = 1.22, 95% CI: 1.12-1.33), and BMI (OR = 1.03, 95% CI: 1.02-1.05) were significantly associated with female infertility. CoI had the best diagnostic performance (area under the ROC curve 0.628, 95% CI: 0.597-0.658).

CONCLUSIONS

Obesity-related indices were positively linked to infertility risk among women in the United States. These indices serve as valuable tools for assessing female infertility risk.

Association of cardiorenal biomarkers with mortality in metabolic syndrome patients: A prospective cohort study from NHANES

Objectives

Approximately 20%-25% of the global adult population is affected by metabolic syndrome (MetS), highlighting its status as a major public health concern. This study aims to investigate the predictive value of cardiorenal biomarkers on mortality among patients with MetS, thus optimizing treatment strategies.

Methods

Utilizing data from the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2004, we conducted a prospective cohort study involving 2369 participants diagnosed with MetS. We evaluated the association of cardiac and renal biomarkers with all-cause and cardiovascular disease (CVD) mortality, employing weighted Cox proportional hazards models. Furthermore, machine learning models were used to predict mortality outcomes based on these biomarkers.

Results

Among 2369 participants in the study cohort, over a median follow-up period of 17.1 years, 774 (32.67%) participants died, including 260 (10.98%) from CVD. The highest quartiles of cardiac biomarkers (N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and renal biomarkers (beta-2 microglobulin, [β2M]) were significantly associated with increased risks of all-cause mortality (hazard ratios [HRs] ranging from 1.94 to 2.06) and CVD mortality (HRs up to 2.86), after adjusting for confounders. Additionally, a U-shaped association was observed between high-sensitivity cardiac troponin T (Hs-cTnT), creatinine (Cr), and all-cause mortality in patients with MetS. Machine learning analyses identified Hs-cTnT, NT-proBNP, and β2M as important predictors of mortality, with the CatBoost model showing superior performance (area under the curve [AUC] = 0.904).

Conclusion

Cardiac and renal biomarkers are significant predictors of mortality in MetS patients, with Hs-cTnT, NT-proBNP, and β2M emerging as crucial indicators. Further research is needed to explore intervention strategies targeting these biomarkers to improve clinical outcomes.

Associations between novel anthropometric indices and the prevalence of gallstones among 6,848 adults: a cross-sectional study

Background

Traditional anthropometric measures, including body mass index (BMI), are insufficient for evaluating gallstone risk. This study investigated the association between novel anthropometric indices and gallstone risk among 6,848 participants from the National Health and Nutrition Examination Survey in the United States.

Methods

Measures calculated included weight (WT), BMI, waist circumference (WC), waist-to-height ratio (WtHR), conicity index (CI), A Body Shape Index (ABSI), Body Roundness Index (BRI), Abdominal Volume Index (AVI), and Weight-adjusted Waist Index (WWI). Logistic regression and smooth curve fitting assessed the relationships between these indices and gallstones, complemented by receiver operating characteristic (ROC) curve analysis to evaluate their discriminative power.

Results

The results indicated significant differences between study groups, with a positive and independent correlation identified between gallstones and all measures except ABSI. Specifically, per 1 SD increase in WC, WT, BMI, WtHR, and AVI was associated with a 57%, 59%, 52%, 53%, and 53% increased risk of gallstones, respectively. Dose-response analysis confirmed a positive correlation between these indices and gallstone risk. ROC analysis highlighted WtHR and BRI as having superior discriminative abilities (AUC = 0.6703). Further, among participants with a BMI < 30 kg/m2, elevated levels of WT, WtHR, CI, BRI, and WWI significantly increased the risk of gallstones (P < 0.001). Likewise, elevated BMI heightened the risk at low levels of WT, WC, WtHR, BRI, AVI, and CI (P < 0.001).

Conclusion

This study supports the positive association between various anthropometric indicators and gallstones, recommending that newer anthropometric indices be considered more extensively to enhance gallstone prevention and treatment strategies.

Accessing the relationship between six surrogate insulin resistance indexes and the incidence of rapid kidney function decline and the progression to chronic kidney disease among middle-aged and older adults in China: Results from the China health and retirement longitudinal study

AIMS

Insulin resistance is closely related to kidney function decline, but which insulin resistance index could better predict rapid kidney function decline (RKFD) remains unclear. We aimed to evaluate the prospective association between six insulin resistance indexes: Chinese Visceral Adiposity Index (CVAI), Lipid Accumulation Product (LAP), Atherogenic Index of Plasma (AIP), triglyceride-glucose (TyG) index, triglyceride-glucose × Body Mass Index (TyGBMI) and triglyceride-glucose × waist circumference (TyGWC) with RKFD and further the progression to chronic kidney disease (CKD).

METHODS AND MEASUREMENTS

Data were obtained from the China Health and Retirement Longitudinal Study. Participants with normal kidney function (eGFRcr-cys ≥60 ml/min per 1.73 m2) and ≥45 years old were included at the baseline (year 2011). The eGFR was estimated by a combination of serum creatinine and cystatin C. The primary outcome was RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more. Secondary outcome was progression to CKD under the condition of RKFD, defined as an annualized decline in eGFRcr-cys of 5 ml/min per 1.73 m2 or more combined with eGFRcr-cys <60 ml/min per 1.73 m2 at the exit visit. Logistic analysis was applied for analysis of the association between six insulin resistance indexes and RKFD or progression to CKD. We use receiver operating characteristic curves to study the predictive performance of six insulin resistance indexes. Subgroup analysis were conducted by diabetes or hypertension status of the participants.

RESULTS

A total of 3899 participants with normal kidney function were included in this study. After a 3.99 years follow-up, 191 of them ended up with RKFD. Among them, 66 participants progressed to CKD. Logistic analysis showed that per SD increase of all the six insulin resistance indexes were significantly associated with the incidence of RKFD (all P < 0.01), among which, TyGWC had the best predictive value for RKFD. There were significant association between per SD increase of CVAI, LAP, TyGBMI and TyGWC with progression to CKD (all P < 0.01), and CVAI had better predictive role than other indexes. In subgroup analysis, we found that the association between insulin resistance indexes and progression to CKD was more significant in subjects with hypertension or without diabetes. However, no significant differences were observed in the RKFD group.

CONCLUSIONS

In this study we proved six insulin resistance indexes were predictively associated with RKFD in Chinese with normal renal function over age 45. TyGWC is the best insulin resistance index for predicting RKFD. CVAI is the best index for predicting further progression to CKD.

Predictive ability of novel and traditional anthropometric measurement indices for kidney stone disease: a cross-sectional study

BACKGROUND

The aim of our research was to examine the association of novel anthropometric indices (a body shape index (ABSI), waist-to-height ratio (WtHR), conicity index (CI) and body roundness index (BRI)) and traditional anthropometric indices (body mass index (BMI), and waist (WC)) with prevalence of kidney stone disease (KSD) in the general population of United States (U.S.).

METHODS

In this study, we conducted a cross-sectional analysis among the participants in the National Health and Nutrition Examination Survey between the years 2007 and 2020. Weighted multivariable logistic regression analysis, restricted cubic spline (RCS), receiver operating characteristic (ROC) curves, and subgroup analysis were performed to analyze the association of ABSI, BRI, WtHR, CI, BMI and WC with prevalence of KSD.

RESULTS

In total, 11,891 individuals were included in our study. The RCS plot shown that the linear positive association was found between ABSI, BRI, WtHR, CI, BMI and WC and KSD risk. Additionally, the ROC curve demonstrated that the area under the curve of ABSI, BRI, WtHR, and CI was significantly higher than traditional anthropometric indices, including BMI and WC.

CONCLUSIONS

Our study found that the discriminant ability of ABSI, BRI, WtHR, and CI for KSD was higher than BMI and WC. Consequently, ABSI, BRI, WtHR, and CI have the potential to become new indicators for the detection of KSD risk in clinical practice.

Abdominal obesity as assessed by anthropometric measures associates with urinary incontinence in females: findings from the National Health and Nutrition Examination Survey 2005-2018

BACKGROUND

Urinary incontinence (UI) is significantly link to abdominal obesity. This study aimed to assess the association between anthropometric indices of abdominal obesity, including body roundness index (BRI), conicity index (CI), and waist-to-height ratio (WHtR), and UI risk in adult females.

METHODS

We analyzed data from 10, 317 adult females in the National Health and Nutrition Examination Survey (NHANES) database (2005-2018). Weighted multivariable-adjusted regression analysis was conducted to determine the odds ratio (OR) and 95% confidence intervals (CI) for the association between BRI, CI, WHtR, and UI. Stratified analyses revealed the association based on the population type. Receiver operating characteristic curve (ROC) analyses were used to assess the predictive value of UI.

RESULTS

All indices of abdominal obesity investigated were positively and independently associated with the prevalence and severity of three types of UI. After adjusting for all relevant confounding variables, a significantly positive association between BRI and the prevalence of UI were observed (OR quartile 4 vs. quartile 1: urge UI (UUI): 1.93, 95% CI 1.61-2.30; stress UI (SUI): 2.29, 95% CI 1.94-2.70; mixed UI (MUI): 2.26, 95% CI 1.82-2.82; all P < 0.0001, P for trend < 0.0001, respectively), as well as WHtR and CI, which particularly prominent for female in premenopausal. Moreover, a one-unit increment of BRI was significantly associated with an increased severity index of UUI (β: 0.06, 95% CI 0.04-0.09, P < 0.0001), SUI (β: 0.10, 95% CI 0.07-0.13, P < 0.0001) and MUI (β: 0.07, 95% CI 0.04-0.10, P < 0.0001), which this trend was also observed in each subtype of UI for WHtR and CI. Furthermore, the ROC analysis demonstrated a higher diagnostic efficacy of BRI and WHtR compared with BMI in discriminating UI with an AUC of 0.600 for SUI, 0.617 for UUI, and 0.622 for MUI (all P < 0.05).

CONCLUSIONS

An increased BRI, CI, and WHtR are significantly associated with higher prevalence and severity of UI in females.

Association between systemic immune-inflammatory index and diabetes mellitus: mediation analysis involving obesity indicators in the NHANES

Background

Inflammation and obesity have been widely recognized to play a key role in Diabetes mellitus (DM), and there exists a complex interplay between them. We aimed to clarify the relationship between inflammation and DM, as well as the mediating role of obesity in the relationship.

Methods

Based on the National Health and Nutrition Examination Survey (NHANES) 2005-2018. Univariate analyses of continuous and categorical variables were performed using t-test, linear regression, and χ2 test, respectively. Logistic regression was used to analyze the relationship between Systemic Immune-Inflammatory Index (SII) or natural logarithm (Ln)-SII and DM in three different models. Mediation analysis was used to determine whether four obesity indicators, including body mass index (BMI), waist circumference (WC), visceral adiposity index (VAI) and lipid accumulation product index (LAP), mediated the relationship between SII and DM.

Results

A total of 9,301 participants were included, and the levels of SII and obesity indicators (BMI, WC, LAP, and VAI) were higher in individuals with DM (p < 0.001). In all three models, SII and Ln-SII demonstrated a positive correlation with the risk of DM and a significant dose-response relationship was found (p-trend <0.05). Furthermore, BMI and WC were associated with SII and the risk of DM in all three models (p < 0.001). Mediation analysis showed that BMI and WC mediated the relationship between SII with DM, as well as Ln-SII and DM, with respective mediation proportions of 9.34% and 12.14% for SII and 10.23% and 13.67% for Ln-SII (p < 0.001).

Conclusion

Our findings suggest that increased SII levels were associated with a higher risk of DM, and BMI and WC played a critical mediating role in the relationship between SII and DM.

Relationship between Novel Anthropometric Indices and the Prevalence of Abdominal Aortic Calcification: A Large Cross-Sectional Study

Background

The relationship between novel anthropometric indices, specifically a body shape index (ABSI) and body roundness index (BRI), with abdominal aortic calcification (AAC) or severe AAC (SAAC) is unclear. The aim of our study was therefore to investigate possible relationships between novel anthropometric indices and prevalence of AAC and SAAC.

Methods

We obtained U.S. general population data from the National Health and Nutrition Examination Survey between 2013 and 2014. The study used restricted cubic spline (RCS) analysis, multivariable logistic regression modeling, subgroup analysis, and receiver operating characteristic (ROC) curve assessment. We investigated relationships between ABSI or BRI and AAC and SAAC risk. Associations between ABSI or BRI and the degree of AAC were also evaluated using a generalized additive model.

Results

The study cohort was comprised of 1062 individuals. The RCS plots revealed a U-shaped curve associating ABSI with AAC risk. A similar trend emerged for SAAC, where the risk initially increased before subsequently decreasing with rising ABSI levels. Additionally, BRI exhibited a positive correlation with both AAC and SAAC risk. As ABSI and BRI values increased, the degree of AAC also increased. In ROC analysis, ABSI displayed a significantly larger area under the curve compared to BRI.

Conclusions

ABSI is associated with AAC prevalence following a U-shaped curve. Additionally, BRI is positively correlated with AAC risk. ABSI demonstrates a superior discriminative ability for AAC compared to BRI. Therefore, maintaining an appropriate ABSI and BRI may reduce the prevalence of AAC.

Association between weight-adjusted-waist index and chronic kidney disease: a cross-sectional study

AIMS

We aimed to investigate the potential association between weight-adjusted-waist index (WWI) and chronic kidney disease (CKD).

DESIGN AND METHODS

This research examined data collected from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2020. CKD was defined as the low estimated glomerular filtration rate (eGFR) or the existence of albuminuria (urinary albumin-to-creatinine ratio (ACR) ≥ 30mg/g). Low-eGFR was described as eGFR < 60 mL/min/1.73m2. The associations between WWI with CKD, albuminuria, and low-eGFR were examined using generalized additive models and weighted multivariable logistic regression models. We also analyzed the associations of other obesity indicators with CKD, albuminuria, and low-eGFR, including body mass index (BMI), waist-to-height ratio (WHtR), waist circumference(WC), height, and weight. The receiver operating characteristic (ROC) curves were used to assess and compare their diagnostic abilities.

RESULTS

Males made up 48.26% of the total 40,421 individuals that were recruited. The prevalences of CKD, albuminuria, and low-eGFR were 16.71%, 10.97%, and 7.63%, respectively. WWI was found to be positively linked with CKD (OR = 1.42; 95% CI: 1.26, 1.60). A nonlinear connection between WWI and CKD was found using smooth curve fitting. Additionally, a higher prevalence of albuminuria is linked to a higher level of WWI (OR = 1.60; 95% CI: 1.40, 1.82). Different stratifications did not substantially influence the connection between WWI and CKD, albuminuria, and low-eGFR, according to subgroup analysis and interaction tests. We observed higher height was related to higher low-eGFR prevalence (OR = 1.05; 95% CI: 1.03, 1.06). ROC analysis revealed that WWI had the best discrimination and accuracy for predicting CKD and albuminuria compared to other obesity indicators (BMI, WHTR, WC, height and weight). In addition, height had the highest area under the curve (AUC) value for predicting low-eGFR.

CONCLUSION

WWI is the best obesity indicator to predict CKD and albuminuria compared to other obesity indicators (BMI, WHTR, WC, height, and weight). WWI and CKD and albuminuria were found to be positively correlated. Furthermore, height had the strongest ability to predict low-eGFR. Therefore, the importance of WWI and height in assessing kidney health in US adults should be emphasized.

Body roundness index is related to the low estimated glomerular filtration rate in Chinese population: A cross-sectional study

BACKGROUND

Kidney disease is related to visceral obesity. As a new indicator of obesity, body roundness index (BRI) has not been fully revealed with kidney disease. This study's objective is to assess the relationship between estimated glomerular filtration rate (eGFR) and BRI among the Chinese population.

METHODS

This study enrolled 36,784 members over the age of 40, they were from 7 centers in China by using a random sampling method. BRI was computed using height and waist circumference, eGFR ≤ 90 mL/min/1.73 m² was considered to indicate low eGFR. To lessen bias, propensity score matching was employed, multiple logistic regression models were utilized to examine the connection between low eGFR and BRI.

RESULTS

The age, diabetes and coronary heart disease rates, fasting blood glucose, and triglycerides were all greater in participants with low eGFR. The BRI quartile was still positively connected with low eGFR after controlling for confounding variables, according to multivariate logistic regression analysis. (OR [95%CI] Q2:1.052 [1.021-1.091], OR [95%CI] Q3:1.189 [1.062-1.284], OR [95%CI] Q4:1.283 [1.181-1.394], P trend < 0.001). Stratified research revealed that the elders, women, habitual smokers, and those with a history of diabetes or hypertension experienced the connection between BRI level and low eGFR. According to ROC, BRI was able to detect low eGFR more accurately.

CONCLUSION

Low eGFR in the Chinese community is positively connected with BRI, which has the potential to be used as an effective indicator for screening kidney disease to identify high-risk groups and take appropriate measures to prevent subsequent complications.

Associations between novel anthropometric measures and the prevalence of hypertension among 45,853 adults: A cross-sectional study

AIMS

Traditional anthropometric measures, including body mass index (BMI), are insufficient for evaluating the risk of hypertension. We aimed to investigate the association between novel anthropometric indices and hypertension risk in a large population in the United States.

METHODS

Forty-five thousand eight hundred fifty-three participants from the National Health and Nutrition Examination Survey (NHANES) (1999-2018) were enrolled. Social demographic information, lifestyle factors, blood biochemical measurements and anthropometric indices, including body weight, body mass index (BMI), waist circumference, waist-to-height ratio (WtHR), conicity index (CI), a body shape index (ABSI), body roundness index (BRI) and lipid accumulation product (LAP) were collected. Multivariable logistic regression and restricted cubic spline were adopted to investigate the associations between hypertension risk and anthropometric indices. We also performed receiver operating characteristic (ROC) curve analyses to further evaluate the discriminatory powers of anthropometric measurements for screening hypertension risk. Moreover, participants were randomly assigned to the training group and the validation group in a ratio of 3 to 1. A nomogram model based on anthropometric measures was established and validated in the training group and validation group, respectively.

RESULTS

All of the anthropometric measurements investigated were positively and independently associated with the hypertension risk. Among all anthropometric indices, per-SD increment in ABSI had the highest OR (OR: 3.4; 95% CI: 2.73-4.24) after adjusting for age, sex, race/ethnicity, education, smoking, drinking, diabetes, and eGFR. Moreover, results from restricted cubic splines revealed the non-linear association between anthropometric measurements and hypertension risk. In ROC analyses, CI had superior discriminatory power for hypertension (area under the curve: 0.71; 95% CI: 0.706-0.715; optimal cutoff value: 1.3) compared with other indices. Nomogram model based on age, sex, diabetes, CI and LAP showed favorable predicting ability of hypertension risk with an AUC (95% CI) in training group of 80.2% (79.7-80.6%), and the AUC (95% CI) in validation group was 79.5% (78.3-80.1%). Meanwhile, calibration plot showed good consistency.

CONCLUSIONS

Anthropometric measurements including BMI, WtHR, CI, ABSI, BRI and LAP are closely associated with hypertension risk in the present study. For better prevention and treatment of hypertension, more attention should be paid to anthropometric indices, especially novel anthropometric indices.