Estimate of prevalent diabetes from cardiometabolic index in general Chinese population: a community-based study

Association between cardiometabolic index and the incidence of stroke: a prospective nationwide cohort study in China

Objectives

Cardiometabolic index (CMI), based on triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio and waist-to-height ratio (WHtR), has been recognized as a novel and practical marker for the assessment of cardiometabolic risk. However, the relationship between CMI and the incidence of stroke remains to be elucidated. This investigation aimed to explore the association between CMI and stroke incidence.

Methods

The investigation included 6,633 individuals aged over 45 years from the China Health and Retirement Longitudinal Study. Logistic regressions and restricted cubic spline regression were uitilized to determine the relationship between CMI and the incidence of stroke. Weighted quantile sum regression was used to offer a comprehensive explanation of the CMI by calculating the weights of triglyceride-glucose (TG), high-density lipoprotein cholesterol (HDL-C), weight, and height.

Results

During the 9-year follow-up, 827 (12%) incident stroke participants were identified. With CMI as a continuous variable, the OR (95% CI) for the risk of incident stroke was 1.09 (1.01-1.19) (p = 0.047) after adjusting for potential confounders, indicating a significant link between increased CMI and an elevated incidence of stroke. Additionally, when CMI was categorized into quartiles, compared to the first quartile, the incident stroke was significantly higher in the fourth quartile (OR 1.57, 95%CI 1.22-2.04, p <0.001). The association between CMI and stroke incidence was nonlinear (p overall=0.002, p non-linear = 0.006). TG emerged as the primary contributor when the weights were assigned to the constituent elements of the CMI (weight = 0.645).

Conclusions

The CMI was independently associated with stroke incidence in middle-aged and elderly Chinese populations. Long-term CMI monitoring is of great importance for early identification and prevention of stroke, with significant implications for clinical practice.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01530-3.

Association of cardiometabolic index with all-cause and cardiovascular mortality among middle-aged and elderly populations

The Cardiometabolic Index (CMI) is a well-recognized risk factor for a range of cardiovascular diseases and diabetes mellitus. However, the population-level characteristics of CMI and its potential association with mortality risk among individuals over 40 years of age have not been investigated. This study aims to assess the association between CMI and both all-cause and cardiovascular mortality among the middle-aged and elderly population. This cohort study utilized data from 3752 American adults extracted from the Sleep Heart Health Study (SHHS) conducted from 1995 to 2011. The CMI was calculated using the waist-to-height ratio, triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C). The primary outcomes were all-cause mortality and cardiovascular mortality, with mortality data sourced from the SHHS Linked Mortality File. Kaplan-Meier survival curves and Cox regression models were employed to assess the prognostic value of the CMI. Among the 3752 American adults, the mean (SD) age was 65.9 (10.1) years, and 1969 (52.5%) were women. The mean (SD) CMI was 0.914 ± 0.939. Over an average follow-up period of 10.7 years, there were 926 all-cause deaths and 289 cardiovascular deaths. Participants were categorized into three groups based on their CMI levels: tertile (T) 1: 0.315 ± 0.0994; T2: 0.680 ± 0.128; T3: 1.75 ± 1.23. Multivariate Cox proportional hazards analysis showed that elevated CMI was significantly associated with all-cause mortality (HR 1.215, 95% CI 1.032-1.43 for T2; HR 1.309, 95% CI 1.115-1.537 for T3) and cardiovascular mortality (HR 1.305, 95% CI 0.971-1.755 for T2; HR 1.457, 95% CI 1.091-1.947 for T3). After adjusting for confounders, elevated CMI remained significantly associated with all-cause mortality (HR 1.315, 95% CI 1.098-1.575 for T3) and cardiovascular mortality (HR 1.562, 95% CI 1.124-2.17 for T3). Kaplan-Meier survival curves indicated significantly worse outcomes for participants in the higher CMI tertiles for both all-cause mortality (log-rank p = 0.0035) and cardiovascular mortality (log-rank p = 0.035). This national cohort study found that CMI is significantly associated with both all-cause and cardiovascular mortality among American adults aged over 40. These findings suggest that CMI could be a valuable tool for identifying high-risk individuals, thereby aiding in the implementation of targeted preventive strategies.

Diabetes mediates the relationship between cardiometabolic index and kidney stones: a cross-sectional study

Previous studies have shown that diabetes is one of the risk factors for kidney stone formation. The Cardiometabolic Index (CMI) is a composite index used to assess an individual's cardiovascular health and metabolic status. CMI has been associated with several metabolic diseases. However, current evidence on the association between CMI and kidney stone risk is limited. The primary objective of this study was to investigate the association between CMI and kidney stones in US adults and to analyze whether diabetes mediates the association. Using data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 and March 2018, this study examined the association between CMI and kidney stones incidence in US adults. Data were analyzed using a variety of statistical methods, including multifactorial logistic regression, subgroup analysis, restricted cubic spline curves (RCS), saturated threshold effects analysis, and mediated effects analysis. A total of 10,609 subjects were included in this study, of which 972 patients were diagnosed with kidney stones. The results of multifactorial logistic regression analysis after fully adjusting for confounding covariates showed a significant positive association between CMI and kidney stones, with an odds ratio (OR) of 1.29 and a 95% confidence interval (CI) of (1.16,1.44). In addition, there was a non-linear positive association between CMI and kidney stones. The results of mediation analysis showed that diabetes mellitus had a mediating role of 15.3% in the correlation between CMI and kidney stones. The findings of this study indicate that elevated CMI levels are associated with an increased risk of kidney stone formation, with diabetes playing a mediating role. These findings indicate that maintaining CMI within the lower range and addressing glycemic regulation is crucial for the prevention of kidney stones.

Association between cardiometabolic index and frailty among patients with diabetes mellitus: a cross-sectional study

Background

Cardiometabolic index (CMI) is a novel marker that can assess metabolic status. Studies have found that people with diabetes mellitus (DM) are at high risk of developing frailty. However, there is a lack of evidence between CMI and the risk of frailty in patients with DM. Therefore, the aim of this study was to investigate the association between CMI and frailty in patients with DM.

Methods

This study utilized data from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Weighted multivariate logistic regression was conducted in this study to explore the association between CMI and frailty status in patients with DM. In addition, subgroup analyses and interaction analyses were conducted to assess heterogeneity between different subgroups. Subsequently, restricted cubic spline (RCS) was also used to test for non-linear relationships.

Results

This study ultimately included 2,761 patients with DM. Weighted multivariate logistic regression showed that, after adjusting all covariates, an increase in the level of CMI was associated with an increased risk of being in a frailty status in patients with DM (OR = 1.12, 95% CI = 1.04-1.22, p = 0.005). Dividing CMI into tertiles, the risk of frailty in patients in the highest tertile (Q3) was higher than that of patients in Q1 (OR = 1.56, 95% CI = 1.18-2.07, p = 0.002). The non-linear relationship between CMI and the risk of frailty in DM patients was further confirmed by RCS analysis.

Conclusion

This study found that the higher the CMI, the higher the risk of frailty in DM patients. Maintaining a healthy low-fat dietary pattern and properly controlling blood lipid levels may reduce the risk of frailty in patients with DM.

Association between cardiometabolic index and female infertility: A population-based study

BACKGROUND

One of the risk indicators of infertility is obesity. The cardiometabolic index (CMI) comprises obesity and blood lipids and is regarded as a novel indicator for evaluating obesity. Nevertheless, it is unclear whether it has any connection to infertility. This study set out to investigate the association between infertility and CMI.

METHODS

Based on cross-sectional data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES), infertility and CMI statistics with complete information were selected. This study investigated the correlation between CMI and infertility using multivariate logistic regression analyses and subgroups. Use fitted smooth curves and threshold effect analysis to describe the nonlinear association between CMI and infertility.

RESULTS

202 (13.31%) among the 1720 participants that got involved in the investigation were female infertile. Among the three models, the outcomes confirmed a positive correlation between CMI levels and the incidence of infertility (OR = 1.12, 95% CI: 1.01-1.24). Additionally, significant relationships were maintained in subgroup analysis (p > 0.05). Smooth curve fitting indicated a nonlinear positive connection between CMI and infertility, and an inflection point of 0.93 (log-likelihood ratio P < 0.05) was shown by threshold effect analysis.

CONCLUSION

Our findings suggest a significant relationship between CMI and infertility in American females. This helps identify high-risk groups for infertility, informing clinical practice and public health policy to improve metabolic and reproductive health.

Correlation between cardiometabolic index and female infertility: a cross-sectional analysis

BACKGROUND

Obesity and adverse lipid profile leads to female infertility. The cardiometabolic index (CMI) is a promising indicator for predicting obesity-related diseases. The correlation between CMI and female infertility merits further investigation.

METHODS

The data for this study were acquired from the 2013-2020 National Health and Nutrition Examination Survey (NHANES), with 2333 women enrolled. The cardiometabolic index (CMI) of each participant was calculated as the ratio of triglycerides and high-density lipoprotein cholesterol multiplied by waist-to-height ratio. Weighted multivariate logistic regression models were used to assess the independent correlation between the log-transformed CMI and infertility. Subgroup analyses were carried out to assess the reliability of the findings. Interaction tests were employed to determine whether variables affected infertility by interacting with log CMI.

RESULTS

A total of 2333 participants aged 18-45 years were enrolled, 274 of whom were infertile. Log CMI of the infertility group was significantly higher than that of the non-infertility group (P < 0.001). After adjustment for potential confounders, women with higher CMI were at an increased risk of infertility (OR = 2.411, 95% CI: 1.416-4.112), and this correlation was still consistent in subgroups aged under 35 years (P < 0.001). Furthermore, restricted cubic spline analysis showed a positive non-linear relationship between log CMI and infertility.

CONCLUSIONS

Cardiometabolic index levels are positively correlated with increased risk of infertility in American females. Our study demonstrates the predictive capacity of CMI for female infertility.

Cardiometabolic index and the risk of new-onset chronic diseases: results of a national prospective longitudinal study

Background

The cardiometabolic index (CMI) has emerged as a novel marker for evaluating the distribution and dysfunction of visceral adipose tissue, yet its correlation with numerous diseases, particularly new-onset chronic conditions, remains underexplored. Therefore, we aim to explore the association of cardiometabolic index (CMI) and new-onset chronic diseases.

Methods

The analysis utilized data from the China Health and Retirement Longitudinal Study, with a baseline in 2011 and follow-ups biennially until 2020. Fourteen new-onset chronic diseases were diagnosed based on self-report, and separate cohorts were created for each disease. CMI was calculated as triglycerides/high-density lipoprotein cholesterol multiplied by the waist-to-height ratio. Cox proportional hazards models were used to assess the association between CMI and new-onset chronic diseases, while restricted cubic spline (RCS) models were employed to explore potential nonlinear effects. Additional and sensitivity analyses included Kaplan-Meier survival curves, subgroup analyses, multiple imputations, and exclude outcome events at the first follow-up.

Results

Higher levels of CMI were associated with an increased risk of new-onset hypertension (HR=1.05, 95% CI=1.04-1.06, P<0.001), diabetes (HR=1.08, 95% CI=1.06-1.09, P<0.001), dyslipidemia (HR=1.07, 95% CI=1.06-1.09, P<0.001), liver disease (HR=1.05, 95% CI=1.03-1.07, P<0.003), and stroke (HR=1.04, 95% CI=1.02-1.06, P<0.001), although the association with stroke was not significant after adjusting for confounders (HR=1.02, 95% CI=1.00-1.05, P=0.054). Participants in the highest quartile of CMI had a significantly higher risk of these diseases compared to those in the lowest quartile. RCS analyses showed a significant nonlinear relationship between CMI and the risk of these diseases above.

Conclusions

CMI showed a significant positive association with the risk of new-onset chronic diseases such as hypertension, diabetes, dyslipidemia, and liver disease. Future applications of CMI hold promise as an effective marker for early identification of chronic disease risk.

Associations of the cardiometabolic index with insulin resistance, prediabetes, and diabetes in U.S. adults: a cross-sectional study

BACKGROUND

The cardiometabolic index (CMI) is a novel metric for assessing cardiometabolic health and type 2 diabetes mellitus (DM), yet its relationship with insulin resistance (IR) and prediabetes (preDM) is not well-studied. There is also a gap in understanding the nonlinear associations between CMI and these conditions. Our study aimed to elucidate these associations.

METHODS

We included 13,142 adults from the National Health and Nutrition Examination Survey (NHANES) 2007-2020. CMI was calculated by multiplying the triglyceride-to-high density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Using weighted multivariable linear and logistic regression explored the relationships of CMI with glucose metabolism markers, IR, preDM, and DM. Nonlinear associations were assessed using generalized additive models (GAM), smooth curve fittings, and two-piecewise logistic regression.

RESULTS

Multivariate regression revealed positive correlations between CMI and glucose metabolic biomarkers, including FBG (β = 0.08, 95% CI: 0.06-0.10), HbA1c (β = 0.26, 95% CI: 0.22-0.31), FSI (β = 4.88, 95% CI: 4.23-5.54), and HOMA-IR (β = 1.85, 95% CI: 1.56-2.14). There were also significant correlations between CMI and increased risk of IR (OR = 3.51, 95% CI: 2.94-4.20), preDM (OR = 1.49, 95% CI: 1.29-1.71), and DM (OR = 2.22, 95% CI: 2.00-2.47). Inverse nonlinear L-shaped associations were found between CMI and IR, preDM, and DM, with saturation inflection points at 1.1, 1.45, and 1.6, respectively. Below these thresholds, increments in CMI significantly correlated with heightened risks of IR, preDM, and DM.

CONCLUSIONS

CMI exhibited inverse L-shaped nonlinear relationships with IR, preDM, and DM, suggesting that reducing CMI to a certain level might significantly prevent these conditions.

Non-linear associations between cardiovascular metabolic indices and metabolic-associated fatty liver disease: A cross-sectional study in the US population (2017-2020)

The cardiometabolic index (CMI) is an emerging and effective indicator for predicting the presence of metabolic-associated fatty liver disease (MAFLD). This study aims to investigate the relationship between CMI and MAFLD using data from NHANES 2017-2020. In this cross-sectional study, a total of 3,749 subjects were included. The study conducted a thorough analysis of CMI with three multivariate logistic regression models, subgroup analyses, and restricted cubic splines (RCS) were utilized. Using multifactorial logistic regression as the primary method of analysis, we found that a higher CMI was also significantly associated with an increased risk of MAFLD (OR = 1.45, 95% CI (1.05-2.01)). This result was further visualized by the RCS curve: There was a non-linear positive correlation between CMI and MAFLD incidence (the turning point is CMI = 0.4554). These findings were strongly reinforced by subsequent subgroup and sensitivity analyses. There is a robust positive relationship between the CMI and the risk of MAFLD, providing valuable clinical benefits for early detection and screening of MAFLD. It is important to highlight the presence of a non-linear association between CMI and MAFLD, with an inflection point identified at CMI = 0.4554.

The relationship between cardiometabolic index and infertility in American adults: a population-based study

Background

Infertility is a fertility disorder caused by various factors, with lipid metabolism playing a crucial role in its development. The cardiometabolic index (CMI), which combines blood lipids (TG/HDL-C) and obesity-related parameters (WHtR), is a new quantitative indicator. This study used NHANES data to investigate the relationship between CMI and the incidence of infertility.

Methods

We utilized data from women who took part in the National Health and Nutrition Examination Survey (NHANES) from 2015 to March 2020 to calculate the CMI index. Subsequently, we used multivariate logistic regression, smooth curve fitting, and subgroup analysis to investigate the relationship between the CMI index and infertility.

Results

The logistic regression model revealed a significant positive correlation between the CMI index and infertility, even after adjusting for all confounding variables (OR=3.23, 95%CI: 1.55-6.73, p=0.0017). This association remained consistent across all subgroups (p>0.05 for all interactions). Smooth curve fitting demonstrated a positive nonlinear relationship between CMI and infertility. However, the CMI index had limited diagnostic power for infertility (AUC=0.60, 95%CI: 0.56-0.65). However, the CMI-BMI index combined with BMI had good predictive performance (AUC=0.722, 95%CI: 0.676-0.767).

Conclusion

The CMI index shows a positive correlation with infertility, but its diagnostic value is restricted. The combination with BMI has good diagnostic value. Further investigation is required to determine the effectiveness of the CMI index as an early indicator of infertility.

Association between cardiometabolic index and testosterone among adult males: a cross-sectional analysis from National Health and Nutrition Examination Survey 2013-2016

Background

Cardiometabolic index (CMI) is a well-promising indicator for predicting obesity-related diseases. Testosterone decline and deficiency importantly affect men's health, and may be associated with obesity and excessive deposition of visceral adipose tissue. We aimed to explore the association between CMI and serum testosterone in US adult males.

Methods

The present cross-sectional study was conducted among adult males with complete data about CMI and testosterone in 2013-2016 National Health and Nutrition Examination Survey (NHANES). CMI was calculated as follows: triglyceride (TG) (mmol/L)/high-density lipid-cholesterol (HDL-C) (mmol/L) × waist-to-height ratio (WHtR). Multivariable regression and subgroup analyses were conducted to explore the association between CMI and testosterone.

Results

We included 2,209 male participants for the final analysis. After adjusting for confounders, CMI was found to show a negative correlation between testosterone [minimally adjusted model: β=-10.56, 95% confidence interval (CI): -12.76, -8.36, P<0.001, fully adjusted model: β=-0.04 (-4.88, 4.81), P=0.99]. Multivariate-adjusted beta also showed testosterone levels were significantly lower in the two highest CMI groups (Q3, Q4) compared to the lowest group (Q1). In the subgroup populations, the relationship between CMI and testosterone was affected by age, race, education level, hypertension, and smoking status (P-interaction <0.05). Furthermore, receiver operating characteristic (ROC) curve analysis indicated that triglyceride-glucose-body mass index (TyG-BMI) (0.67, 95% CI: 0.65, 0.70) was the best predictor of low testosterone (results), although CMI was comparable in its predictive value (0.68, 95% CI: 0.65, 0.71).

Conclusions

Higher CMI scores were associated with lower testosterone levels in adult males in the United States, with this correlation being influenced by factors such as age, race, education level, hypertension, and smoking status. CMI was comparable to other metabolic indexes for predicting testosterone deficiency, although TyG-BMI was the best overall predictor.

Nomogram for predicting risk of mild renal dysfunction among general residents from rural Northeast China

Background and objectives

Cumulative evidence confirms that mild renal dysfunction (MRD) is correlated with many cardiovascular risk factors and increases cardiovascular morbidity and mortality. The purpose of this study was to establish an effective nomogram for predicting the risk of MRD in the rural population of Northeast China.

Methods

We analyzed the reports of 4944 subjects from the Northeast China Rural Cardiovascular Health Study (NCRCHS). All the participants completed the questionnaires, anthropometric measurements, and blood tests during the baseline study (2012-2013) and the follow-up study during 2015-2017 (an average of 4.6 years). The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate the estimated glomerular filtration rate (eGFR), and eGFR in the range of 60-90 mL/min/1.73m2 was defined as MRD.

Results

The study revealed that a total of 889 subjects (18.0%) had MRD. Multivariate logistic analysis showed that annual income, abdominal obesity, hypertension, hyperglycemia, and frequent tea consumption were the independent risk factors (P < 0.05) for MRD. Thereafter, a nomogram with an area under the receiver operating characteristic curve (AUC) of 0.705 was constructed to accurately predict MRD. The calibration plot also showed an excellent consistency between the probability of prediction and observation.

Conclusion

We constructed a nomogram based on epidemiological data, which could provide an individual prediction of MRD with good accuracy.

Correlation of cardiometabolic index and sarcopenia with cardiometabolic multimorbidity in middle-aged and older adult: a prospective study

Background

Research has demonstrated that sarcopenia and visceral obesity are significant risk factors for chronic disease in middle-aged and older adults. However, the relationship between sarcopenia, the cardiac metabolic index (CMI), a novel measure of visceral obesity, and cardiometabolic multimorbidity (CMM) remains unclear. In this study, data from the China Longitudinal Study of Health and Retirement (CHARLS) were analyzed to investigate the association between sarcopenia and CMI with CMM in the middle-aged and older adult population.

Methods

The study included 4,959 participants aged 45 and over. Sarcopenia was defined using the criteria of the Asian Sarcopenia Working Group 2019. CMM is defined as having two or more of the following conditions: physician-diagnosed heart disease, diabetes, stroke, and/or hypertension. CMI was calculated using the formula: CMI = (TG/HDL-C) × WHtR. To explore the association between CMI and sarcopenia and CMM, cox proportional risk regression models were used.

Results

The median age of all participants was 57 years, with 47.1% being male. Over the 8-year follow-up, 1,362 individuals developed CMM. The incidence of CMM was 8.7/1,000 person-years in the group without sarcopenia or high CMI, 17.37/1,000 person-years in those with high CMI, 14.22/1,000 person-years in the sarcopenia group, and 22.34/1,000 person-years in the group with both conditions. After adjusting for covariates, the group with both sarcopenia and high CMI had a significantly increased risk of CMM (HR 2.48, 95% CI 1.12-5.51) and heart disease (HR 2.04, 95% CI 1.05-3.98). Among those over 65 years, sarcopenia was discovered to be associated with an increased risk of CMM [HR (95% CI: 4.83 (1.22, 19.06)]. The risk of CMM was further increased to 7.31-fold (95% CI:1.72, 31.15) when combined with high CMI.

Conclusions

The combination of sarcopenia and high CMI is associated with an increased risk of developing CMM. Early identification and intervention of sarcopenia and CMI not only enable the development of targeted therapeutic strategies but also provide potential opportunities to reduce the morbidity and mortality of CMM.

Wakabayashi & Daimon cardiometabolic index as an indicator to assess risk in adults. A systematic review

OBJECTIVE

To analyze the Wakabayashi & Daimon (2015) equation, as a predictive indicator of cardiometabolic diseases and its comparison with other indices.

DESIGN

A systematic review was carried out between January and March 2023, according to the PRISMA statement.

DATA SOURCE

Scopus, Web of Science, and PubMed databases were reviewed using "cardiometabolic index" (CMI) as the search term.

STUDY SELECTION

The following inclusion criteria were determined: studies in adults with cardiometabolic diseases using the Wakabayashi & Daimon (2015) CMI formula in different populations; studies that validate or compare the equation or that demonstrate the effects of the intervention.

DATA EXTRACTION

Of the 11 selected articles, the characteristics of the population, type of study, indicators for the validation of the CMI, the reported statistics and the conclusions that were recorded in a comparative table were obtained.

RESULTS AND CONCLUSIONS

Odds ratio, hazard ratio, sensitivity, and specificity were used to assess associations, risk, effectiveness, and validity of the tests, indicating favorable relationships between the factors analyzed and the results obtained. Validation and probabilistic analysis of the CMI were performed against diverse diseases such as obesity [Man >60y=AUC=0.90 (0.75-1.00) (p=0.01), Se=100, Sp=81.8, YI=0.82 and OR 4.66 and Women >60y=AUC=0.95 (0.88-1.00), p=0.001, Se=90.0, Sp=100, YI=0.90 and OR=36.27]; cardiovascular diseases [AUC=0.617, Se=0.675, Sp=0.509; HR=1.48 (1.33, 1.65), p=<0.001], among others. In conclusion CMI is a new utility index that broadly identifies the presence of risk that leads to cardiometabolic diseases in adults.

Association of adiposity indicators with cardiometabolic multimorbidity risk in hypertensive patients: a large cross-sectional study

Background

Cardiometabolic multimorbidity (CMM) has emerged as a prominent public health concern. Hypertensive patients are prone to develop comorbidities. Moreover, the accumulation of visceral adipose tissue is the main cause for the development of cardiometabolic diseases. The cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI) not only assess adipose tissue mass but also reflect adipose tissue dysfunction. So far, no study has been reported to evaluate the association of CMI, LAP, VAI, and CVAI with CMM risk in hypertensive patients. Therefore, this study aimed to assess the association between these adiposity indicators and the risk of CMM among Chinese hypertensive patients.

Methods

In this cross-sectional study, a total of 229,287 hypertensive patients aged 35 years and older were included from the National Basic Public Health Service Project. All participants underwent a face-to-face questionnaire survey, physical examination, and the collection of fasting venous blood samples. Multivariable logistic regression models were performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic curve was utilized to evaluate the identification ability for CMM.

Results

After adjusting for confounders, each 1-standard deviation increase in CMI, LAP, VAI, and CVAI was associated with a 14%, 8%, 12%, and 54% increased risk of CMM, respectively. When comparing the highest quartile of these indicators with the lowest quartile, individuals in the highest quartile of CMM, LAP, VAI, and CVAI had a 1.39-fold (95% CI 1.30, 1.48), 1.28-fold (95% CI 1.19, 1.37), 1.37-fold (95% CI 1.29, 1.46), and 2.56-fold (95% CI 2.34, 2.79) increased risk of CMM after adjusting for potential confounders. Notably, a nonlinear association was observed for CMI, LAP, and VAI with the risk of CMM (all P nonlinearity < 0.001). CVAI exhibited the highest area under the receiver operating characteristic curve (AUC) among all the included adiposity indices in this analysis.

Conclusion

This study indicated the significant positive association of CMI, LAP, VAI, and CVAI with the risk of CMM in hypertensive patients. Among these indicators, CVAI demonstrated the most robust performance in predicting CMM risk and may serve as a valuable tool for identifying CMM risk in Chinese hypertensive patients.

Cardiometabolic index is associated with increased depression: A population-based study

BACKGROUND AND AIM

Depression is a common and complex psychiatric disorder, and lipid metabolism plays an important role in the development of psychiatric disorders such as depression. Cardiometabolic index (CMI) is a novel index that synthesizes two quantitative indicators of blood lipids (triglyceride(TG)/high-density lipoprotein cholesterol (HDL-C)) and human obesity-related parameters (waist height ratio (WHtR)). This study used NHANES data to explore the correlation between CMI and the incidence of depression.

METHODS AND RESULTS

Based on the data of the National Health and Nutrition Examination Survey (NHANES) 2011-2018, multivariate logistic regression, sensitivity analysis, and smooth curve fitting were used to study the relationship between CMI and depression. Subgroup analysis and interaction tests were used to investigate whether the association was stable in different populations. CMI was positively associated with depression in 7229 participants aged >20 years. In the fully adjusted model, each unit increase in CMI was associated with 36 % higher likelihood of depression symptoms [1.36(1.16,1.59)]. Participants in the highest quartile of CMI had a 62 % higher risk of depression than participants in the lowest quartile [1.62(1.17,2.23)]. This positive correlation was more pronounced in those with hypertension.

CONCLUSIONS

CMI was associated with a higher PHQ-9 score and an increased likelihood of depression among US adults. Further large-scale prospective studies are still need to analyze the role of CMI in depression.

Non-linear associations of cardiometabolic index with insulin resistance, impaired fasting glucose, and type 2 diabetes among US adults: a cross-sectional study

Background

Cardiometabolic index (CMI) is a novel indicator for predicting the risk of obesity-related diseases. We aimed to determine the relationships of CMI with insulin resistance (IR), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM) using NHANES data from 1999 to 2020.

Methods

After CMI values were estimated, weighted univariate and multivariate logistic regression analyses were used to ascertain whether CMI was an independent risk indicator for IR, IFG, and T2DM. Furthermore, stratified analyses and interaction analyses were carried out to investigate the heterogeneity of correlations across various subgroups. Subsequently, restricted cubic splines (RCS) were used to examine nonlinear relationships.

Results

21,304 US adults were enrolled in our study, of whom 5,326 (22.38%) had IR, 4,706 (20.17%) had IFG, and 3,724 (13.02%) had T2DM. In the studied population, a higher CMI index value was significantly associated with an elevated likelihood of IR, IFG, and T2DM. In the RCS regression model, the relationship between CMI and IR, IFG, and T2DM was identified as nonlinear. A nonlinear inverted U-shaped relationship was found between CMI and IFG, and an inverse L-shaped association was observed between CMI and IR, CMI and T2DM. The cut-off values of CMI were 1.35, 1.48, and 1.30 for IR, IFG, and T2DM, respectively.

Conclusion

Our results indicate that CMI was positively correlated with an increase in IR, IFG, and T2DM in the studied population. CMI may be a simple and effective surrogate indicator of IR, IFG, and T2DM.

Relationship Between Cardiometabolic Index and Insulin Resistance in Patients with Type 2 Diabetes

Purpose

Cardiometabolic index (CMI) has been suggested as innovative measures for assessing the cardiometabolic status. However, there is a lack of relevant studies on exploring the relationship between CMI and insulin resistance (IR). Consequently, this study aims to examine the relationship between CMI and IR in subjects with type 2 diabetes mellitus (T2DM).

Patients and Methods

A cross-sectional study was performed on 2493 patients with T2DM (including 1505 males and 988 females). IR was measured through the homeostatic model assessment of insulin resistance (HOMA-IR), which was defined as HOMI-IR≥2.69. The relationship between CMI and IR was evaluated with Spearman's correlation, ROC analysis, multiple logistic regression, generalized smooth curve fitting and subgroup analysis.

Results

CMI was correlated with HOMA-IR in patients with T2DM (Spearman correlation coefficient = 0.391 in females and 0.346 in males, P<0.001). Through the multiple logistic regression analysis, CMI was significantly correlated with IR (OR=1.30, 95% CI=1.15-1.47 in males and OR=1.62, 95% CI=1.32-1.99 in females). In addition, a non-linear correlation between CMI and IR risk was identified. The AUC of CMI (AUC = 0.702 for males and 0.733 for females, all p < 0.01) was the largest compared with traditional indexes of adiposity and blood lipids. According to the subgroup analysis, the two had a more significantly positive correlation in females, the elderly and subjects with HbA1c < 7%.

Conclusion

In patients with T2DM, elevated CMI is significantly correlated with IR, as a useful index of IR.

Relationship Between Cardiometabolic Index in Early Pregnancy and Hypertensive Disorder Complicating Pregnancy

Background This study aimed to examine the cardiometabolic index during early pregnancy in individuals with hypertension-complicating pregnancy, especially preeclampsia. Additionally, this study sought to determine the relationship between cardiometabolic index and the incidence of varying degrees of preeclampsia. Methodology This study included 289 pregnant women diagnosed with preeclampsia who were registered and delivered at our hospital. These women were assigned to the preeclampsia group. Additionally, a group of 289 healthy pregnant women of identical gestational ages within the same time frame was included for comparison. Clinical data on pregnancy, including body mass index (BMI), blood pressure, waistline, triglyceride levels, and cardiometabolic index, were compared between the two groups. An analysis was conducted to examine the association between early pregnancy cardiometabolic index and the occurrence of preeclampsia. Results There was a significant association between the quartile of cardiometabolic index and the proportion of preeclampsia patients (p < 0.001). Furthermore, after controlling for age and BMI, the risk of preeclampsia remained significantly elevated and was associated with the cardiometabolic index. Conclusions A positive correlation was observed between cardiometabolic index during early pregnancy and the occurrence of preeclampsia.

Evaluation of the frequency of metabolic syndrome and assessment of cardiometabolic index among men with erectile dysfunction: a prospective cross-sectional study

Purpose

Recently, an association has been observed between metabolic syndrome and erectile dysfunction (ED). This study aimed to evaluate the cardiometabolic index (CMI) in patients with ED.

Methods

This cross-sectional study was performed on 144 patients with ED who were referred to a urology clinic in Rasht, Iran, from 2019 to 2021. Metabolic syndrome was evaluated according to National Cholesterol Education Program Expert Panel (NCEP) and Adult Treatment Panel III (ATP III) criteria which are considered three positive criteria from five. Also, the ED severity was classified as weak, moderate, and severe based on the five-item International Index of Erectile Function (IIEF5) questionnaire.

Results

The mean age of participants was 53.46 ± 10.58 years. 56.9% had abdominal obesity, 48.6% had hypertriglyceridemia, 34.7% had low HDL-C, 55.6% had hypertension and 56.9% had elevated fasting blood sugar (FBS). 43.8% had diabetes and 13.2% had cardiovascular disease. The mean CMI was 2.51 ± 1.57. The prevalence of metabolic syndrome was 50.7%. Body mass index (BMI) was significantly associated with metabolic syndrome and CMI (P = 0.001). The severity of ED had a significant relationship with high FBS in patients. CMI and components of abdominal obesity, hypertriglyceridemia, and low HDL-C had no statistically significant relationship with ED. However, the incidence of moderate and severe ED increased with increasing the number of metabolic syndrome components.

Conclusion

ED is not significantly associated with metabolic syndrome and CMI, however, the severity of this disorder increases with increasing the number of components of metabolic syndrome.

Sex-Specific Contribution of Cardiometabolic Index in Predicting Metabolic Dysfunction-Associated Fatty Liver Disease: Insights from a General Population

Background and Objective

Evidence suggests that cardiometabolic index (CMI) has been identified as a novel obesity-related index associated with diabetes, hypertension, and cardiovascular disease. Current evidence suggests that the differences in sex hormones and regional fat distribution in both sexes are directly correlated with metabolic dysfunction-associated fatty liver disease (MAFLD) risk. This study aimed to investigate the diagnostic value of CMI in MAFLD in both sexes.

Methods

This retrospective study included 6107 subjects who underwent annual health check-ups from March 2021 to January 2022. CMI was calculated by multiplying the ratio of triglycerides and high-density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Multivariable logistic regression analysis and restricted cubic spline were used to investigate the association of CMI and MAFLD risk. Receiver operating characteristic curve analysis was conducted for the exploration of the diagnostic accuracies of obesity-related indicators. Areas under the curves (AUCs) with 95% CIs were calculated.

Results

Prevalence of MAFLD increased with elevated quartiles of CMI in both sexes. The median (IQR) age was 46.00 (18.00) years. Multivariate logistic regression analyses showed that higher CMI was independently associated with MAFLD, in which every additional standard deviation (SD) of CMI increased the risk of MAFLD (OR=2.72, 95% CI:2.35-3.15 for males; OR=3.26, 95% CI:2.36-4.51 for females). Subjects in the fourth quartile of CMI had the highest odds of MAFLD for males (OR=15.82, 95% CI:11.84-21.14) and females (OR=22.60, 95% CI:9.52-53.65)(all P for trend<0.001). Besides, CMI had a non-linearity association with MAFLD (all P for non-linearity<0.001). Furthermore, CMI exhibited the largest AUC compared to other obesity-related indexes in terms of discriminating MAFLD in males (AUC=0.796, 95% CI:0.782-0.810) and females (AUC=0.853, 95% CI:0.834-0.872).

Conclusion

CMI was a convenient indicator for the screening of MAFLD among Chinese adults. Females with high CMI had a better diagnostic value for MAFLD than males.

Cardiometabolic index is associated with urinary albumin excretion and renal function in aged person over 60: Data from NHANES 2011-2018

PURPOSE

Cardiometabolic index (CMI) is recently considered to have certain significance in the screening of diabetes, atherosclerosis, and renal dysfunction. Therefore, this study intends to explore the relationship between CMI and the risk of albuminuria.

METHODS

This is a cross-sectional study involving 2732 elderly people (age ≥ 60). The research data are from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018. Calculate CMI index: Triglyceride (TG) (mmol/L)/ High density lipid-cholesterol (HDLC) (mmol/L) × WHtR.

RESULTS

The CMI level in microalbuminuria group was significantly higher than that in normal albuminuria group (P < 0.05 or P < 0.01), whether in the general population or in diabetes and hypertensive population respectively. The proportion of abnormal microalbuminuria increased gradually with the increase of CMI tertile interval (P < 0.01). Correlation analysis showed that CMI was positively correlated with urinary albumin-creatinine ratio (UACR), blood urea nitrogen (BUN), and serum creatinine (Scr), and negatively correlated with estimated glomerular filtration rate (eGFR). With the occurrence of albuminuria as the dependent variable, weighted logistic regression analysis showed that CMI was an independent risk factor for microalbuminuria. Weighted smooth curve fitting showed that CMI index was linearly related to the risk of microalbuminuria. Subgroup analysis and interaction test showed that they participated in this positive correlation.

CONCLUSIONS

Obviously, CMI is independently associated with microalbuminuria, suggesting that CMI, a simple indicator, can be used for risk assessment of microalbuminuria, especially in diabetes patients.

Dietary Intervention on Overweight and Obesity after Confinement by COVID-19

BACKGROUND

Obesity has become a public health problem in our society and is associated with many diseases, including type 2 diabetes mellitus, cardiovascular diseases, dyslipidemia, respiratory diseases, and cancer. Several studies relate weight loss in obese patients to improved anthropometric measurements and cardiometabolic risk. The objective of our study was to evaluate anthropometric changes, analytical parameters, insulin resistance, fatty liver, and metabolic scales, after a personalized weight loss program, through dietary advice to increase adherence to the Mediterranean diet and a motivational booster via mobile SMS messaging.

METHODS

Intervention study on a sample of 1964 workers, in which different anthropometric parameters were evaluated before and after dietary intervention: the metabolic score of insulin resistance; non-alcoholic fatty liver disease using different scales; metabolic syndrome; atherogenic dyslipidemia; and the cardiometabolic index. A descriptive analysis of the categorical variables was performed, by calculating the frequency and distribution of the responses for each one. For quantitative variables, the mean and standard deviation were calculated, since they followed a normal distribution. Bivariate association analysis was performed by applying the chi-squared test (corrected by Fisher's exact statistic when conditions required it) and Student's t-test for independent samples (for comparison of means).

RESULTS

The population subjected to the Mediterranean diet improved in all the variables evaluated at 12 months of follow-up and compliance with the diet.

CONCLUSIONS

Dietary advice on a Mediterranean diet and its reinforcement with reminder messages through the use of mobile phones may be useful to improve the parameters evaluated in this study and reduce the cardiometabolic risk of patients.

The nonlinear correlation between the cardiometabolic index and the risk of diabetes: A retrospective Japanese cohort study

BACKGROUND

The cardiometabolic index (CMI) has been proposed as a novel indicator of cardiometabolic status. However, evidence on the relationship between CMI and diabetes mellitus (DM) risk was limited. Our study aimed to explore the relationship between CMI and DM risk among a large cohort of Japanese adults.

METHODS

This retrospective cohort study recruited 15453 Japanese adults without diabetes at baseline who underwent physical examinations at the Murakami Memorial Hospital between 2004 and 2015. Cox proportional-hazards regression was applied to evaluate the independent relationship between CMI and diabetes. Our study performed a generalized smooth curve fitting (penalized spline technique) and an additive model (GAM) to determine the non-linear relationship between CMI and DM risk. In addition, a set of sensitivity analyses and subgroup analyses were employed to evaluate the relationship between CMI and incident DM.

RESULTS

After adjusting for confounding covariates, CMI was positively related to the DM risk in Japanese adults (HR: 1.65, 95%CI: 1.43-1.90, P<0.0001). A series of sensitivity analyses were also employed in this study to guarantee the reliability of the findings. In addition, our study discovered a non-linear association between CMI and diabetes risk. CMI's inflection point was 1.01. A strong positive association between CMI and diabetes incidence was also discovered to the left of the inflection point (HR: 2.96, 95%CI: 1.96-4.46, P<<0.0001). However, their association was not significant when CMI was higher than 1.01 (HR: 1.27, 95%CI: 0.98-1.64, P=0.0702). Interaction analysis showed that gender, BMI, habit of exercise, and smoking status interacted with CMI.

CONCLUSION

Increased CMI level at baseline is associated with incident DM. The association between CMI and incident DM is also non-linear. A high CMI level is associated with an increased risk for DM when CMI is below 1.01.

Association of lipid accumulation product with type 2 diabetes mellitus, hypertension, and mortality: a systematic review and meta-analysis

Purpose

Novel anthropometric measures are simple, applicable, and inexpensive tools for cardiovascular risk assessment. This study evaluates the association of lipid accumulation product (LAP) with hypertension, type 2 diabetes mellitus (T2DM), and all-cause mortality, and compares it with other anthropometric measures.

Methods

PubMed, Web of Science, EMBASE, and Scopus were systematically searched for articles published until May 15, 2021. We included all the studies that had measured LAP predictability for T2DM, all-cause mortality, and hypertension with no limitation in comorbidities and follow-up duration. We assessed the predictability measures of LAP for the aforementioned outcomes. We also performed a meta-analysis on four articles on mortality using an inverse variance method by the "meta" package in R software.

Results

Twenty-nine studies were included in the review after applying the eligibility criteria. The hazard ratio for all-cause mortality per one standard deviation increment of LAP was 1.24 (95% confidence interval [CI]: 1.00-1.53; P = 0.0463) in females, and 1.07 (95% CI: 0.74-1.57; P = 0.709) in males. All included studies found a direct association between LAP with T2DM and hypertension. However, studies used different cut-off points for LAP. Most studies found that LAP was superior in predicting T2DM and hypertension compared to conventional indices, e.g., body mass index and waist circumference. We found that LAP may have higher prognostic significance in females compared to males.

Conclusion

LAP is an inexpensive method to evaluate the risk of all-cause mortality, T2DM, and hypertension, and could outperform conventional anthropometric indices in this regard.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-022-01114-z.

Transition of cardiometabolic status and the risk of type 2 diabetes mellitus among middle-aged and older Chinese: A national cohort study

AIMS/INTRODUCTION

The cardiometabolic index (CMI) has been proposed as a novel indicator of cardiometabolic status. This study aimed to investigate the effects of CMI and its longitudinal transitions on the development of type 2 diabetes mellitus in middle-aged and older Chinese.

MATERIALS AND METHODS

We used data from the China Health and Retirement Longitudinal Study (2011-2018). CMI was calculated as the product of the waist circumference to height ratio and the triglyceride to high-density lipoprotein cholesterol ratio. At baseline in 2011, the subjects were classified into low- and high-CMI groups, and then divided into four transition patterns during follow-up, i.e. maintained-low, low-to-high, high-to-low, and maintained-high CMI. The hazard ratios (HRs) of different transition patterns for type 2 diabetes mellitus were calculated using multivariable Cox frailty models.

RESULTS

During 2011-2018, 7,347 participants were included. Participants with a high-CMI at baseline had a significantly higher risk of new-onset type 2 diabetes mellitus than those with a low-CMI (HR = 1.78, 95% CI:1.55-2.05). For subjects with a low-CMI at baseline, the risk of developing type 2 diabetes mellitus increased by 75% if their CMI status changed to high during follow-up (HRlow-to-high  = 1.75, 95% CI:1.35-2.28). Meanwhile, for subjects with a maintained-high CMI, no significant risk reduction for type 2 diabetes mellitus was found when their CMI changed to low status (HRhigh-to-low  = 0.77, 95% CI: 0.58-1.01).

CONCLUSIONS

Baseline CMI levels and longitudinal CMI transition patterns were associated with a higher risk of type 2 diabetes mellitus. Early anti-lipid measures should be taken to prevent type 2 diabetes mellitus in middle-aged and older Chinese.

Associations of the Cardiometabolic Index with the Risk of Cardiovascular Disease in Patients with Hypertension and Obstructive Sleep Apnea: Results of a Longitudinal Cohort Study

Purpose

We aimed to explore the relationship between the cardiometabolic index (CMI) and cardiovascular disease (CVD) and its subtypes (coronary artery disease and stroke) in patients with hypertension and obstructive sleep apnea (OSA).

Methods

We conducted a retrospective cohort study enrolling 2067 participants from the Urumqi Research on Sleep Apnea and Hypertension study. The CMI was calculated as triglyceride to high‐density lipoprotein cholesterol ratio × waist‐to‐height ratio. Participants were divided into three groups (T1, T2, and T3) according to the tertile of CMI. The Kaplan-Meier method helped to calculate the cumulative incidence of CVD in different groups. We assessed the association of CMI with the risk of CVD and CVD subtypes by estimating hazard ratios (HRs) and 95% confidence intervals (CIs) using Cox models.

Results

During a median follow-up of 6.83 years (interquartile range: 5.92-8.00 years), 326 incident CVD were identified, including 121 incident stroke and 205 incident coronary heart disease (CHD). Overall, after adjusting for confounding variables, CMI was positively associated with the risk of new-onset CVD (per SD increment, adjusted HR: 1.31; 95% CI: 1.20, 1.43), new-onset CHD (per SD increment, adjusted HR: 1.33; 95% CI: 1.20, 1.48), and new-onset stroke (per SD increment, adjusted HR: 1.27; 95% CI: 1.10, 1.47). Similar results were obtained in various subgroup and sensitivity analyses. Adding CMI to the baseline risk model for CVD improved the C-index (P < 0.001), continuous net reclassification improvement (P < 0.001), and integrated discrimination index (P < 0.001). Similar results were observed for CHD and stroke.

Conclusion

There was a positive association between CMI levels and the risk of new-onset CVD in patients with hypertension and OSA. This finding suggests that CMI may help identify people at high risk of developing CVD.

Sex-specific contribution of lipid accumulation product and cardiometabolic index in the identification of nonalcoholic fatty liver disease among Chinese adults

Background

Lipid accumulation product (LAP) and cardiometabolic index (CMI) are two novel obesity-related indexes associated with enhancing metabolic disease (MD) risk. Current evidences suggest that the differences in sex hormones and regional fat distribution in both sexes are directly correlated with MD and nonalcoholic fatty liver disease (NAFLD) risk. Hence, NAFLD incidences reflect sex differences. Herein, we examined the accuracy of LAP and CMI in diagnosing NAFLD in both sexes.

Methods

Overall, 14,407 subjects, who underwent health check-up in the northeastern China, were enrolled in this study, and their corresponding LAP and CMI were calculated. Abdominal ultrasonography was employed for NAFLD diagnosis. Multivariate analyses were analyzed potential correlations between LAP and/or CMI and NAFLD. Odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated. Receiver operating characteristic curve analyses was executed for the exploration of the diagnostic accuracies. Areas under the curves (AUCs) with 95%CIs were calculated.

Results

NAFLD prevalence increased with elevated quartiles of LAP and CMI in both sexes. In multivariate logistic regression analyses, LAP and CM expressed as continuous variables or quartiles, significantly correlated with NAFLD. The ORs for the top versus bottom quartile of LAP and CMI for NAFLD were 13.183 (95%CI = 8.512–20.417) and 8.662 (95%CI = 6.371–11.778) in women and 7.544 (95%CI = 5.748–9.902) and 5.400 (95%CI = 4.297–6.786) in men. LAP and CMI exhibited larger AUCs, compared to other obesity-related indexes in terms of discriminating NAFLD. The AUCs of LAP and CMI were 0.860 (95%CI = 0.852–0.867) and 0.833 (95%CI = 0.825–0.842) in women and 0.816 (95%CI = 0.806–0.825) and 0.779 (95%CI = 0.769–0.789) in men.

Conclusions

LAP and CMI are convenient indexes for the screening and quantification of NAFLD within a Chinese adult population. Their associations with NAFLD are substantially greater in women than men.

Association between the cardiometabolic index and non-alcoholic fatty liver disease: insights from a general population

Background

Emerging evidence suggests that cardiometabolic index (CMI) is closely related to diabetes, hypertension, stroke, cardiovascular disease, and kidney disease, which implies that CMI has the value as an indicator of metabolic diseases. However, data on the relationships between CMI and non-alcoholic fatty liver disease (NAFLD) risks have not been reported. This study is designed to examine the association between CMI and NAFLD in the general population.

Methods

The current study included 14,251 subjects whose CMI was the product of triglyceride/high-density lipoprotein cholesterol ratio and waist-to-height ratio. Linear regression was used to analyze the correlation between baseline information and CMI, logistic regression was used to study the relationship between CMI and NAFLD, and subgroup analysis was used to explore potential high-risk groups.

Results

After adjusted for potential confounding factors, higher CMI was independently associated with NAFLD, in which every additional standard deviation (SD) of CMI increased the risk of NAFLD by 28% (OR 1.28 per SD increase, 95% CI 1.19–1.37, P for trend < 0.0001). There were also significant differences in CMI-related NAFLD risk among different ages and genders, in which the CMI-related NAFLD risk in young people was significantly higher than that in other age groups (OR = 2.63 per SD increase for young people, OR = 1.38 per SD increase for young and middle-aged people, OR = 1.18 per SD increase for middle-aged and elderly people; OR = 1.14 per SD increase for elderly people, P for interaction = 0.0010), and the CMI-related NAFLD risk in women was significantly higher than that in men (OR = 1.58 per SD increase for women, OR = 1.26 per SD increase for men, P for interaction = 0.0045).

Conclusions

Current studies have found that after excluding potential confounding factors, higher CMI in the general population is independently associated with NAFLD risk.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02099-y.

Cardiometabolic index: A new predictor for metabolic associated fatty liver disease in Chinese adults

OBJECTIVE

Cardiometabolic index (CMI) is a well promising indicator for predicting obesity-related diseases, but its predictive value for metabolic associated fatty liver disease (MAFLD) is unclear. This study aimed to investigate the relationship between CMI and MAFLD and to evaluate the predictive value of CMI for MAFLD.

METHODS

A total of 943 subjects were enrolled in this cross-sectional study. CMI was calculated by multiplying the ratio of triglycerides and high-density lipoprotein cholesterol (TG/HDL-C) by waist-to-height ratio (WHtR). Multivariate logistic regression analysis was used to systematically evaluate the relationship between CMI and MAFLD. Receiver operating characteristic (ROC) curves were used to assess the predictive power of CMI for MAFLD and to determine the optimal cutoff value. The diagnostic performance of high CMI for MAFLD was validated in 131 subjects with magnetic resonance imaging diagnosis.

RESULTS

Subjects with higher CMI exhibited a significantly increased risk of MAFLD. The odds ratio for a 1-standard-deviation increase in CMI was 3.180 (2.102-4.809) after adjusting for various confounding factors. Further subgroup analysis showed that there were significant additive interactions between CMI and MAFLD risk in gender, age, and BMI (P for interaction < 0.05), and the area under the ROC curve(AUC) of CMI for predicting MAFLD were significantly higher in female, young, and nonobese subgroups than that in male, middle-aged and elderly, and obese subgroups (all P < 0.05). Moreover, among nonobese subjects, the AUC of CMI was significantly higher than that of waist circumference, BMI, TG/HDL-C, and TG (all P < 0.05). The best cutoff values of CMI to diagnose MAFLD in males and females were 0.6085 and 0.4319, respectively, and the accuracy, sensitivity, and specificity of high CMI for diagnosing MAFLD in the validation set were 85.5%, 87.5%, and 80%, respectively.

CONCLUSIONS

CMI was strongly and positively associated with the risk of MAFLD and can be a reference predictor for MAFLD. High CMI had excellent diagnostic performance for MALFD, which can enable important clinical value for early identification and screening of MAFLD.

Triglyceride Glucose Index Is More Closely Related to Hyperuricemia Than Obesity Indices in the Medical Checkup Population in Xinjiang, China

BACKGROUND

Hyperuricemia (HUA) is a metabolic anomaly with an increased incidence rate, causing a global medical burden. Several studies have confirmed that obesity and insulin resistance (IR) are the risk factors for HUA. Reports on the predictive power of different obesity indices for HUA are limited. This study aimed to compare the association between different general, abdominal, and visceral obesity indices and markers of the IR-triglyceride glucose (TyG) index with serum uric acid (SUA) and to assess the ability of these indices to predict HUA.

METHODS

A total of 2243 participants were recruited from Barkol County Hospital and surrounding township hospitals in Xinjiang. Obesity indices, including the atherogenic index of plasma, cardiometabolic index, visceral adiposity index, lipid accumulation product index, a body shape index, body roundness index, waist circumference, waist-to-height ratio, body mass index, and TyG index, were divided into four quartiles. Moreover, partial correlations and logistic regression were used to analyze the association between these indices and SUA. The area under the curve (AUC) and receiver operating characteristic curves were used to analyze the predictive value of these indices for HUA.

RESULTS

After controlling for confounding variables, the association between the TyG index and HUA was stronger than that between the obesity indices in both males and females. The odds ratios (ORs) for HUA in the highest quartile of the TyG index were 2.098 (95% confidence interval, 1.555-2.831) in males and 7.788 (95% CI, 3.581-16.937) in females. For males, the AIP, CMI, VAI, LAP index, and TyG index were able to discriminate HUA, and the TyG index showed the highest AUC value of 0.586 (95% CI, 0.557-0.614; P < 0.001). For females, all indices, except BMI, can discriminate HUA. Moreover, the visceral obesity index CMI showed the highest AUC value of 0.737 (95% CI, 0.691-0.782; P < 0.001). Meanwhile, the TyG index had a relatively high AUC value of 0.728 (95% CI, 0.682-0.773; P < 0.001).

CONCLUSION

The TyG index was significantly related to HUA and was superior to obesity indices in identifying HUA in the medical checkup population in Xinjiang, China.

Comparison of several blood lipid-related indexes in the screening of non-alcoholic fatty liver disease in women: a cross-sectional study in the Pearl River Delta region of southern China

Background

Lipid metabolism disorders play a critical role in the progression of non-alcoholic fatty liver disease (NAFLD). However, the number of studies on the relationships among blood lipid-related indexes and NAFLD is limited, and few studies have emphasized the comparison of blood lipid-related indexes in the same population to identify the optimal index for NAFLD screening. This study aimed to investigate the relationships among several blood lipid-related indexes and NAFLD, and to find the index with the best screening value for NAFLD.

Methods

Based on a general health examination at community health service agencies in the Pearl River Delta region of China in 2015, 3239 women were recruited in this cross-sectional study. The relationships among blood lipid-related indexes and NAFLD were assessed separately by constructing multivariate logistic regression models. Receiver operating characteristic analysis was used to evaluate and compare the screening abilities of the indexes for NAFLD. All data analyses were conducted in SPSS and MedCalc software.

Results

Whether in the crude model or each model adjusted for possible confounding factors, the risk of NAFLD significantly rose with increasing cardiometabolic index (CMI), triglyceride glucose index (TyG), triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C), total cholesterol (TC) to HDL-C ratio (TC/HDL-C) and low-density lipoprotein (LDL-C) to HDL-C ratio (LDL-C/HDL-C). Moreover, the area under the curve (AUC) of CMI was 0.744, which was better than that of TyG (0.725), TG/HDL-C (0.715), TC/HDL-C (0.650), and LDL-C/HDL-C (0.644) (P < 0.001). In addition, the optimal cut-off points were 0.62 for CMI, 8.55 for TyG, 1.15 for TG/HDL-C, 4.17 for TC/HDL-C, and 2.22 for LDL-C/HDL-C.

Conclusions

CMI is easy to obtain, is a recommended index in the screening of NAFLD in women and may be useful for detecting populations that are at high risk of NAFLD.

Body Adiposity Index Is Predictive of Weight Loss after Roux-en-Y Gastric Bypass

BACKGROUND/AIMS

Roux-en-Y gastric bypass (RYGB) is one of the most effective therapies for morbid obesity, yet some patients who have taken the surgery still undergo insufficient weight loss. Visceral adiposity index (VAI), lipid accumulation product (LAP), body adiposity index (BAI), and cardiometabolic index (CMI) have been regarded as clinical indicators of adiposity phenotypes that associated closely with obesity-related metabolic diseases. However, no studies have evaluated the relationship between these indexes and weight loss after bariatric surgery. In this prospective study, we aimed to evaluate whether VAI, LAP, BAI, and CMI would predict postoperative weight loss outcomes after RYGB.

METHODS

This study included 38 men and 67 women who have undergone RYGB between January 2017 and May 2018 and recorded their %TWL (percent of total weight loss), %EBMIL (percent of excess body mass index loss), %EWL (percent of excess weight loss), anthropometric indices, and biochemical parameters before and 12 months after the surgery. In addition, VAI, LAP, BAI, and CMI were measured with anthropometric measures or lipid profiles using related equations and analyzed with metabolic characteristics.

RESULTS

Subjects with lower BAI (<32.54 in men and 37.39 in women) displayed higher %EBMIL and %EWL 12 months after surgery. BAI was independently associated with %EWL 12 months after surgery in both men and women (both p < 0.05). The area under the receiver operating characteristic curve for BAI was significantly higher (0.773 in men and 0.818 in women) than VAI, LAP, and CMI.

CONCLUSIONS

BAI serves as a reliable surrogate marker of the weight loss outcome after RYGB. The predictivity of adiposity indexes in beneficial outcomes after weight loss therapies is of important referential value for the implementation and optimization of individualized and refined weight loss treatments for obese patients.

Evaluation of Anthropometric Indices and Lipid Parameters to Predict Metabolic Syndrome Among Adults in Mexico

BACKGROUND

Metabolic syndrome (MetS) is a cluster of conditions that increases the risk of cardiovascular disease (CVD) and is related to genetic background, dietary habits, and lifestyle. Anthropometric indices and lipid parameters have been shown to be simple and useful tools in clinical practice for predicting MetS. The aim of the present study was to evaluate the differential magnitudes of anthropometric characteristics (waist circumference and body mass index [BMI]) and lipid parameters, namely, lipid accumulation product (LAP), cardiometabolic index (CMI), and Castelli Risk Index (CRI-I), to estimate MetS, usingappropriate cut-off values, among adults from a public hospital in Yucatan, Mexico.

METHODS

A cross-sectional study among 250 adults (77 men, 173 women) was carried out in the Regional High Speciality Hospital of the Yucatan Peninsula (HRAEPY) in Merida, Yucatan. MetS was diagnosed using standard criteria (central obesity, arterial hypertension, hyperglycemia, and dyslipidemia), and derived parameters (LAP, CMI, and CRI-I) were calculated. Binary logistic regression analysis-based receiver operating characteristics (ROC) curves were used to predict MetS.

RESULTS

Of the 250 participants, 48% had MetS. High prevalences of overweight (35.2%) and obesity (48.8%) were found in the sample. The CMI and LAP were found to be the best parameters in the prediction of MetS in men and women. The optimal cut-off values of the parameters were higher in men and decreased with advancing age.

CONCLUSION

The CMI and LAP were shown to be the most effective indicators to diagnose MetS among adults from Yucatan, Mexico.

Estimate of prevalent hyperuricemia by systemic inflammation response index: results from a rural Chinese population

OBJECTIVES

Hyperuricemia is a common metabolic disease that is intimately correlated with inflammation. Our study aimed to investigate the value of systemic inflammation response index as a novel inflammatory marker to estimate hyperuricemia in the rural Chinese population.

METHODS

This cross-sectional study used the data of 8,095 Chinese men and women aged ≥35 years from the 2012-2013 Northeast China Rural Cardiovascular Health Study.

RESULTS

The overall prevalence of hyperuricemia was 12.84%. After fully adjusting for potential confounders, each SD increase of SIRI in men and women caused a 21.4% and 37.0% additional risk, respectively, for hyperuricemia. Moreover, smooth curve fitting and subgroup analyses corroborated the linearity and robustness of this correlation. ROC analysis showed the ability of SIRI to estimate hyperuricemia was significantly improved in females (0.741 vs 0.745, P = 0.043), but not in males (0.710 vs 0.714, P = 0.105). The net reclassification improvement (NRI, 0.120 in men vs 0.166 in women) and integrated discrimination improvement (IDI, 0.002 in men vs 0.006 in women) showed a significant improvement for both genders.

CONCLUSIONS

Our present study suggests a linear and robust relationship between SIRI and prevalent hyperuricemia, which implicates the value of SIRI to optimize the risk stratification and prevention of hyperuricemia.

Impact of monocyte to high-density lipoprotein ratio on prevalent hyperuricemia: findings from a rural Chinese population

BACKGROUND

Monocyte to high-density lipoprotein cholesterol ratio (MHR) is a novel inflammatory marker that has been used to predict various inflammation-related diseases. This study aims to explore the association between MHR and prevalent hyperuricemia in a rural Chinese population.

METHODS

8163 eligible participants (mean age: 54.13 years, males: 45.71%) from northeast China were enrolled in this cross-sectional study between 2012 to 2013. MHR was determined as blood monocyte count ratio to high-density lipoprotein cholesterol concentration.

RESULTS

The prevalence of hyperuricemia was 12.86%. After adjusting for potential confounding factors, per SD increase of MHR caused a 25.2% additional risk for hyperuricemia, and the top quartile of MHR had an 82.9% increased risk for hyperuricemia compared with the bottom quartile. Additionally, smooth curve fitting and subgroup analyses showed a linear and robust association between MHR and prevalent hyperuricemia respectively. Finally, after introducing MHR into the established model of risk factors, the AUC displayed a significant improvement (0.718 vs 0.724, p = 0.008). Furthermore, Category-free net reclassification improvement (0.160, 95% CI: 0.096-0.224, P < 0.001) and integrated discrimination improvement (0.003, 95% CI: 0.002-0.005, P < 0.001) also demonstrated significant improvements.

CONCLUSIONS

The present study suggests that MHR was positively and independently correlated with prevalent hyperuricemia among rural Chinese adults. Our results also implicate an important value for MHR in optimizing the risk stratification of hyperuricemia.

Synergistic interaction of hyperuricemia and hypertension on reduced eGFR: insights from a general Chinese population

OBJECTIVES

Hyperuricemia and Hypertension are two independent risk factors of renal function damage. Our research aimed to investigate the synergistic interaction between hyperuricemia and hypertension toward reduced eGFR.

METHODS

Our analyses included 11,694 participants from a cross-sectional population-based Northeast China Rural Cardiovascular Health Study. Interaction was assessed on both multiplicative and additive scales.

RESULTS

The prevalence of reduced estimated glomerular infiltration rate (eGFR) was 2.11% in our population. After adjustment of age, sex, race, education level, family income, current smoking and drinking status, body mass index, total cholesterol, high-density lipoprotein cholesterol, and diabetes, subjects with both hyperuricemia and hypertension suffered from a 11.004 (95% CI: 7.080-17.102) times risk of reduced eGFR than the healthy reference group, greater than that in participants with only hyperuricemia (5.741, 95% CI: 3.045-10.825) or hypertension (1.145, 95% CI: 0.764-1.715). Furthermore, additive interaction between hyperuricemia and hypertension was statistically significant and synergistic (relative excess risk due to interaction: 5.118, 95% CI: 0.611-9.624; the attributable proportion due to interaction: 0.465, 95% CI: 0.151-0.779; Synergy index: 2.047, 95% CI: 1.017-4.120). However, our results revealed no significant interaction on the multiplicative scale.

CONCLUSIONS

Hyperuricemia and hypertension may have a synergistic interaction toward renal function loss in addition to their independent impacts. Our findings may provide a straightforward illustration which is easy for the public to realize the hazard of coexistent hypertension and hyperuricemia on renal injury.

Capacity of different anthropometric measures to predict diabetes in a Chinese population in southwest China: a 15-year prospective study

AIM

To investigate whether conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product compared with waist circumference could predict future diabetes in a 15-year prospective study.

METHODS

The data were collected in 1992 and recollected in 2007 from the same group of 687 individuals. Anthropometric indices and biochemical data were obtained. Cox's proportional hazards regression models were used to estimate the hazard ratios of anthropometric measures. The discriminatory power of anthropometric measures for incident diabetes were assessed by Harrell's C-statistic.

RESULTS

During follow-up, 74 participants were newly diagnosed with diabetes. In multivariable Cox regression analysis after adjusting potential for confounders, log₁₀ -conicity index [HR: 1.67 (95% CI: 1.31-2.11) per sd; P < 0.0001], log₁₀ -abdominal volume index [HR: 1.95 (95% CI: 1.50-2.55) per sd; P < 0.0001], log₁₀ -body adiposity index [HR: 1.82 (95% CI: 1.33-2.50) per sd; P < 0.0001], log₁₀ -body roundness index [HR: 2.16 (95% CI: 1.63-2.88) per sd; P < 0.0001], log₁₀ -cardiometabolic index [HR: 1.70 (95% CI: 1.39-2.09) per sd; P < 0.0001], log₁₀ -lipid accumulation product [HR: 2.06 (95% CI: 1.56-2.73) per sd; P < 0.0001] and log₁₀ -waist circumference [HR: 1.99 (95% CI: 1.51-2.46) per sd; P < 0.0001] were significantly associated with incident diabetes. Additionally, lipid accumulation product had the highest Harrell's C-statistic at 0.715 (95% CI: 0.656-0.775), followed by body roundness index at 0.714 (95% CI: 0.658-0.770) and cardiometabolic index at 0.704 (95% CI: 0.643-0.764) then by waist circumference at 0.701 (95% CI: 0.644-0.759).

CONCLUSIONS

Conicity index, abdominal volume index, body adiposity index, body roundness index, cardiometabolic index and lipid accumulation product were independent predictors of future diabetes. The discriminatory power of body roundness index, cardiometabolic index and lipid accumulation product for diabetes prediction were higher than that of waist circumference.

The impact of monocyte to high-density lipoprotein ratio on reduced renal function: insights from a large population

Aim: To investigate whether monocyte to HDL cholesterol ratio (MHR) can improve the risk stratification of reduced renal function by estimating atherosclerosis. Patients & methods: The cross-sectional study included 8159 subjects (males: 45.73%, mean age: 54.12 years) from Northeast China in 2013. Results: Each standard deviation increase of MHR brought 42.9% additional risk of reduced renal function in males. In females, MHR strongly correlated with reduced renal function before it reached a breakpoint (MHR = 0.25). Additionally, net reclassification improvement identified the value of MHR (0.199; 95% CI: 0.030–0.369; p = 0.021) to improve the risk classification of renal function reduction. Conclusion: This study implicates that MHR is independently associated with reduced renal function and can refine the risk stratification of renal function reduction.