Cardiometabolic index: a new tool for screening the metabolically obese normal weight phenotype

Association of the cardiometabolic index with sarcopenia among U.S. adults: NHANES 2011-2018 findings

BACKGROUND

The cardiometabolic index (CMI), initially devised as a diagnostic tool for diabetes mellitus, has evolved into a composite biomarker for evaluating metabolic syndrome and cardiovascular disease risk. In order to shed light on any possible interactions between sarcopenia and CMI, this study will look at the relationship between the two.

METHODS AND RESULTS

Data from the 2011-2018 National Health and Nutrition Examination Survey (NHANES) were analyzed to investigate the possible link between sarcopenia and CMI. Among 3,185 eligible participants, the weighted prevalence of sarcopenia was 7.84%. A significant positive association emerged between CMI and sarcopenia risk, with each unit increase in CMI was linked with a 12% greater risk of sarcopenia in the fully adjusted model (OR: 1.12; 95% CI: 1.01-1.26). Moreover, dose-response relationships were evident across CMI tertiles (P for trend < 0.05). Subgroup analyses and interaction tests indicated that the positive correlation between CMI and the risk of sarcopenia differs significantly across subgroups defined by education level, sedentary time and CVD status (all P for interaction < 0.05).

CONCLUSIONS

Our findings demonstrate a robust association between elevated CMI levels and increased sarcopenia risk, suggesting CMI's potential utility as a clinical biomarker for sarcopenia risk surveillance. To confirm these results and demonstrate causality, more research is required.

Bridging the gap in obesity research: A consensus statement from the European Society for Clinical Investigation

BACKGROUND

Most forms of obesity are associated with chronic diseases that remain a global public health challenge.

AIMS

Despite significant advancements in understanding its pathophysiology, effective management of obesity is hindered by the persistence of knowledge gaps in epidemiology, phenotypic heterogeneity and policy implementation.

MATERIALS AND METHODS

This consensus statement by the European Society for Clinical Investigation identifies eight critical areas requiring urgent attention. Key gaps include insufficient long-term data on obesity trends, the inadequacy of body mass index (BMI) as a sole diagnostic measure, and insufficient recognition of phenotypic diversity in obesity-related cardiometabolic risks. Moreover, the socio-economic drivers of obesity and its transition across phenotypes remain poorly understood.

RESULTS

The syndemic nature of obesity, exacerbated by globalization and environmental changes, necessitates a holistic approach integrating global frameworks and community-level interventions. This statement advocates for leveraging emerging technologies, such as artificial intelligence, to refine predictive models and address phenotypic variability. It underscores the importance of collaborative efforts among scientists, policymakers, and stakeholders to create tailored interventions and enduring policies.

DISCUSSION

The consensus highlights the need for harmonizing anthropometric and biochemical markers, fostering inclusive public health narratives and combating stigma associated with obesity. By addressing these gaps, this initiative aims to advance research, improve prevention strategies and optimize care delivery for people living with obesity.

CONCLUSION

This collaborative effort marks a decisive step towards mitigating the obesity epidemic and its profound impact on global health systems. Ultimately, obesity should be considered as being largely the consequence of a socio-economic model not compatible with optimal human health.

National cohort study on cardiometabolic index and incident stroke in middle-aged and older adults in China

Background The Cardiometabolic Index (CMI), a novel marker integrating central obesity and lipid metabolism, serves as a comprehensive indicator of metabolic health. While CMI has been linked to metabolic disorders like diabetes and cardiovascular diseases, its role in predicting stroke risk remains unclear. This study examines the association between CMI and stroke risk in Chinese adults aged 45 and older, highlighting its potential as a predictive tool for public health.

METHODS

Data from the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were divided into CMI quartiles. Stroke incidence was the primary endpoint. Cox proportional hazards models evaluated the CMI-stroke risk association. Kaplan-Meier curves compared stroke incidence across quartiles, while restricted cubic splines (RCS) assessed non-linear trends. Subgroup analyses verified robustness.

RESULTS

Among 7,821 participants (47 % male), 418 strokes (5.3 %) occurred over a mean follow-up of 7 years. Higher CMI was significantly associated with increased stroke risk [HR, 1.153 (95 % CI: 1.048-1.269), P = 0.004]. RCS revealed a non-linear rise in stroke risk with increasing CMI (P for nonlinearity = 0.005). No significant interactions were observed between CMI and subgroups (all P > 0.05).

CONCLUSION

Elevated CMI correlates with higher stroke risk in middle-aged and older Chinese adults. Incorporating CMI into routine assessments could improve early stroke prevention strategies, addressing the increasing burden of cerebrovascular disease in aging populations.

Association between volatile organic compounds exposure and cardiometabolic function: a population-based study

Background

The Cardiometabolic Index (CMI) is a new metric used to assess an individual's cardiovascular and metabolic status. Volatile Organic Compounds (VOCs) are common environmental pollutants associated with cardiovascular diseases and lipid metabolism disorders. This study aims to investigate the relationship between VOC exposure and CMI.

Methods

Data from NHANES (2011-2020) were used to assess the impact of VOC exposure on cardiometabolic function. Multivariable linear regression was used to analyze the association between VOCs and the CMI. Restricted cubic spline models were applied to model the nonlinear relationship between VOCs and CMI. BKMR (bayesian kernel machine regression), WQS (weighted quantile sum), and Q-gcomp (quantile g-computation) models were employed to explore the association between VOC mixture exposure and CMI. Subgroup analyses were conducted to investigate the relationship between VOCs and CMI across different subgroups.

Results

Multiple linear regression analysis confirmed the significantly positive associations between the highest quartile concentrations of CEMA, 3HPMA, MHBMA3, and HMPMA compared to the lowest quartile (β = 0.43, 95% CI = 0.20, 0.67, P for trend < 0.001; β = 0.30, 95% CI = 0.05, 0.55, P for trend = 0.006; β = 0.37, 95% CI = 0.14, 0.61, P for trend < 0.001; β = 0.28, 95% CI = 0.01, 0.55, P for trend = 0.010). AAMC and SBMA showed a nonlinear relationship with CMI. Results from mixture exposure models indicated that CEMA contributed most significantly to the impact on CMI. BKMR, WQS, and Q-gcomp models showed a positive trend between overall VOC exposure and CMI. Subgroup analysis revealed significant interactions of BMI and diabetes status in the relationship between VOC exposure and CMI, especially among individuals with BMI ≥ 30 and those with diabetes.

Conclusion

This study found significant positive associations between specific VOC exposures and CMI. Additionally, BMI and diabetes status play important roles in moderating the relationship between VOC exposure and CMI. These findings highlight the potential impact of environmental VOCs on cardiovascular and metabolic health which provides new evidence for public health interventions.

Cardiometabolic index is negatively associated with the risk of sarcopenia in the middle aged and elderly Chinese: the first longitudinal evidence from CHARLS

BACKGROUND

The association between sarcopenia and cardiometabolic index (CMI) among the Chinese elderly adults remains unclear. The present study aimed to examine the association based on a national survey.

METHODS

Data from China Health and Retirement Longitudinal Study (CHARLS, wave 2011 and 2015) were employed. All subjects met the inclusion criteria were classified by the median of CMI. Four logistic regression models were established to explore the cross-sectional and longitudinal associations between CMI and sarcopenia. Subgroups analysis, tendency analysis, etc. were conducted to testify the robustness of the association. The non-linear relationship was explored using restricted cubic spline (RCS).

RESULTS

5,016 participants were enrolled in this study. The ORs of the longitudinal analysis in the models were 0.42(0.34,0.53), 0.37(0.29,0.46), 0.40(0.31,0.51) and 0.42(0.33,0.53)), respectively. Similar results were also found after propensity score matching (PSM), inverse probability weighting (IPTW) and cross-sectional analysis. Moreover, a non-linear relationship was found between CMI and sarcopenia in the total participants (both p for overall and p for non-linear < 0.001).

CONCLUSION

A U-shaped relationship between CMI and sarcopenia risk was found in the middle aged and elderly Chinese, with both deficient and excessive CMI levels showing detrimental effects. Maintaining a moderate CMI significantly diminishes the risk of sarcopenia.

Nonlinear association of cardiometabolic index with hyperuricemia: insights from the NHANES 1999-2018 study

Background

Hyperuricemia, a risk factor for gout and cardiovascular diseases, has been linked to various metabolic disorders. This study investigates the association between the cardiometabolic index (CMI) and hyperuricemia.

Methods

Using the National Health and Nutrition Examination Survey 1999-2018 data from 23,212 participants, we employed survey-weighted logistic regression to quantify the CMI-hyperuricemia relationship. Generalized additive models explored potential nonlinear relationships, with two-piecewise logistic regression identifying inflection points. Stratified analyses across demographic and health subgroups assessed relationship consistency.

Results

We found a significant association between higher CMI and increased hyperuricemia and identified a nonlinear relationship, characterized by a faster risk increase at lower CMI levels and slower at higher levels. This pattern remained consistent across all demographic and health subgroups.

Conclusions

Higher CMI significantly predicts hyperuricemia across diverse populations, with a pronounced nonlinear association. This pattern underscores the importance of early intervention, emphasizing the need for personalized risk assessments and targeted strategies.

Diabetes is the missing link between cardiometabolic index and gallstones: a large cross-sectional study

The cardiometabolic index (CMI), which integrates individual lipid and visceral fat parameters, represents a superior new predictive tool for cardiovascular and metabolic disorders, but its predictive value for gallstones (GS) is unclear. Therefore, the present study used this vacancy to explore the relationship between CMI levels and GS in US adults, assess the mediating role of diabetes mellitus in the pathogenesis of both, and provide new clinical ideas for early prevention and screening of GS in patients with diabetes mellitus. This survey extracted information from the National Health and Nutrition Examination Survey (NHANES) 2017-2020 vintage cycle. Cross-sectional analyses and a variety of statistical techniques were used to analyze the correlation between CMI and GS, including logistic regression, propensity score matching, subject work curves, and restricted cubic spline (RCS). Furthermore, mediation analysis was used to investigate whether and to what extent diabetes mediated the effect of CMI on GS. After analysis of 3,395 participants, a significant positive correlation was observed between elevated CMI levels and increased prevalence of GS In the fully corrected model (Model 4), the prevalence of GS exhibited a 23% increase for every incremental unit rise in logarithmically transformed CM. Mediation analysis showed that diabetes largely mediated the association between CMI and GS, with a mediation ratio of 15.1%. Higher CMI levels are closely linked to a greater occurrence of GS, and diabetes plays a key mediating role in the pathogenesis of both. Addressing dyslipidemia while not neglecting blood glucose levels, and co-management of the two may be a proven way to reduce GS risk.

Exploring the nonlinear association between cardiometabolic index and hypertension in U.S. Adults: an NHANES-based study

BACKGROUND

Hypertension is a prevalent chronic disease affecting over 1.2 billion people worldwide, representing a major modifiable risk factor for cardiovascular diseases. The Waist-to-Height Ratio (WHtR) and Triglyceride to High-Density Lipoprotein Cholesterol (TG/HDL-C) ratio are established metabolic indicators linked to the risk of cardiovascular and metabolic diseases. Recently, a Cardiometabolic Index (CMI), combining WHtR and TG/HDL-C ratios, has been proposed to provide a comprehensive assessment of metabolic health. This study investigates the association between CMI and hypertension using data from the National Health and Nutrition Examination Survey (NHANES).

METHODS

The study utilized NHANES data from nine cycles spanning 2001 to 2018, encompassing 20,049 participants aged over 20. Exclusions were made for individuals with incomplete CMI or hypertension data, and pregnant women. CMI was calculated by multiplying the WHtR by the TG/HDL-C ratio. Hypertension was defined according to American Heart Association guidelines. The relationship between CMI and hypertension was evaluated using multivariate logistic regression analyses, with additional subgroup analyses conducted based on demographic factors. Nonlinear relationships were analyzed using smoothing curve fitting techniques.

RESULTS

The study identified a significant positive correlation between CMI and hypertension risk, with an increase of one unit in CMI associated with a 9% heightened risk of hypertension (OR: 1.09, 95% CI: 1.05, 1.13). The association remained significant across various demographic subgroups. A nonlinear relationship was observed, with a critical CMI threshold of 2.64. Below this threshold, higher CMI values were associated with a progressively higher prevalence of hypertension, whereas beyond this threshold, further increases in CMI did not significantly correlate with an elevated risk of hypertension.

CONCLUSION

The study demonstrates that CMI is significantly associated with hypertension risk and may serve as a valuable tool for early screening and risk assessment, particularly in identifying individuals at higher risk before reaching the critical CMI threshold. These results underscore the importance of addressing metabolic health in the prevention and management of hypertension. Future research should focus on longitudinal studies to establish causality, explore the clinical utility of CMI in hypertension screening, and examine its applicability in diverse populations.

Association of cardiometabolic index and new-onset stroke in middle-aged and elderly Chinese: a national prospective cohort study

BACKGROUND AND AIMS

The Cardiometabolic Index (CMI), a novel metabolic marker, has been associated with various metabolic diseases in previous studies. However, its relationship with stroke risk remains underexplored. This study investigates the potential correlation between CMI and stroke risk among Chinese adults aged 45 and older.

METHODS

In the China Health and Retirement Longitudinal Study (CHARLS), participants were categorized into four groups based on CMI quartiles. The primary outcome was the incidence of new strokes during the follow-up period. A Cox proportional hazards model was used to analyze the relationship between CMI and stroke risk among the elderly. Kaplan-Meier survival analysis compared incidence rates across CMI levels, and restricted cubic splines (RCS) assessed potential non-linear relationships between CMI and stroke. Subgroup analyses verified the robustness of these findings.

RESULTS

The study included 6620 patients (45% male), with 417 new stroke cases reported over an average follow-up of seven years. Multivariate analysis indicated a significant association between increased CMI and higher stroke risk [HR, 1.132 (1.021-1.273), P = 0.003]. The RCS model revealed a nonlinear increase in stroke risk with rising CMI levels (P for nonlinearity = 0.006). No significant interactions were detected between CMI and the selected subgroups (all P values for interaction > 0.05).

CONCLUSION

CMI significantly correlates with stroke risk in the elderly Chinese population, suggesting its potential utility in early risk stratification.

Associations between cardiometabolic index with kidney stones: evidence from NHANES 2007-2018

Background

Kidney stones are a prevalent disorder that is linked to a range of metabolic variables. The cardiometabolic index (CMI) is a newly developed combined measure used to evaluate the state of cardiometabolic health. Nevertheless, the association between CMI and kidney stone remains little investigated.

Methods

In this study, cross-sectional analysis was done on NHANES data from 2007 to 2018. The association between the prevalence of kidney stones and the CMI was investigated using a logistic regression analysis. To look into the nonlinear link between them, we used restricted cubic spline (RCS) analysis. The study was made more reliable and accurate by using sensitivity analysis and subgroup analysis to look for factors that may have contributed to the different results.

Results

A significant association was seen between increased CMI and the prevalence of kidney stones (OR = 1.19, 95% CI: 1.06-1.32). The RCS analysis revealed crucial CMI values that exhibited a robust association within a certain range. Subgroup studies revealed that this link was particularly prominent among those below the age of 50, females, obese, CKD and diabetes patients. The dependability of the study's conclusions was further established using sensitivity analysis.

Conclusion

This study established a notable association between CMI and a higher prevalence of kidney stones, emphasizing the significance of CMI as a comprehensive measure for evaluating metabolic risk. Furthermore, it suggests that monitoring CMI levels could be beneficial in identifying populations with a high prevalence of kidney stones.

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

Background

Visceral fat accumulation and dyslipidaemia are associated with infertility symptoms. The cardiometabolic index (CMI) is a comprehensive quantitative measure of central obesity and dyslipidaemia. However, the link between the female CMI and the couple infertility needs to be explored further. Hence, this study aimed to dissect this connection.

Methods

The study used a cross-sectional approach to select 1,641 female participants from the National Health and Nutrition Examination Survey (NHANES), which was conducted between 2013 and 2020. The natural log-transformed CMI (In-CMI) was used to consider the non-normal distribution of CMI. Logistic regression models adjusted for covariates were employed to investigate the association between the In-CMI and couple infertility.

Results

After adjusting for all covariates, each 1 unit increase in the In-CMI was associated with a 34% increase in the incidence of infertility (odds ratio [OR] 1.34, 95% confidence interval [CI] 1.10-1.64, p = 0.004). In addition, the association remained statistically significant after dividing the In-CMI into tertiles (T1, T2, and T3). The T3 group, with the highest In-CMI, showed higher odds of infertility compared with the T1 group (OR 2.11, 95% CI 1.38-3.23, p < 0.001). Subgroup and interaction analyses revealed that the association between the In-CMI and infertility depended on a history of treatment for pelvic infection (P for interaction <0.05). The inflection point for a positive linear association between In-CMI and infertility was-0.73.

Conclusion

The female CMI is linked to the incidence of couple infertility. Moreover, the female CMI shows significant medical significance for assessing couple infertility risk of childbearing age.

Association between cardiometabolic index and hypertension among US adults from NHANES 1999-2020

Hypertension, a major global health issue and leading cause of death, is often under-assessed by traditional metrics like Body Mass Index which fail to capture comprehensive cardiovascular risks associated with obesity. The Cardiometabolic Index (CMI), which evaluates abdominal obesity and dyslipidemia, offers a more accurate assessment of visceral fat and metabolic dysfunction. In this study, we analyzed data from 45,250 participants from the National Health and Nutrition Examination Survey spanning 1999 to 2020. Using multivariable logistic regression, we explored the association between CMI and hypertension, employing Restricted Cubic Spline analysis to assess non-linear relationships and two-piecewise linear regression to identify threshold effects. Subgroup analyses confirmed the consistency of our findings across various demographic and clinical characteristics. Findings confirmed that hypertensive participants exhibited significantly higher CMI levels (median 0.46 vs. 0.73), with adjusted logistic regression showing a notable association between increased CMI and hypertension prevalence (OR 1.30, 95% CI 1.25-1.35, P < 0.01), characterized by a nonlinear L-shaped curve with a critical threshold identified at a CMI value of 1.37. Subgroup analysis revealed a more pronounced impact of CMI on hypertension in females. These results underscore CMI's potential to enhance cardiovascular risk assessment across diverse U.S. populations.

Association between cardiometabolic index and overactive bladder in adult American women: A cross-sectional study

BACKGROUND

Overactive bladder (OAB) is a common disorder, particularly in women, and its symptoms, including urgency, frequency, and nocturia, can significantly affect quality of life. The cardiometabolic index (CMI) is a novel metabolic risk indicator that has been receiving more attention lately. This study investigated the association between CMI and OAB in adult women.

METHODS

A cross-sectional analysis was performed using data from the National Health and Nutrition Examination Survey (NHANES) covering the years 2007 to 2018, including 6323 female participants. CMI was calculated based on waist-to-height ratio, triglyceride, and HDL cholesterol levels, while OAB was assessed using the overactive bladder symptom score (OABSS). The association between CMI and OAB was evaluated through multivariate logistic regression, generalized additive models (GAM), smoothing curve fitting, and subgroup analysis. We finally included male participants for sensitivity analysis.

RESULTS

A significant positive association was found between female CMI and OAB prevalence (OR = 1.46, 95% CI: 1.29-1.65). When compared to the lowest CMI quartile (Q1), women in the highest CMI quartile were 70% more likely to have OAB (OR = 1.70, 95% CI: 1.42-2.04). Smoothed curve fitting analysis showed a linear association between CMI and OAB. Subgroup analysis revealed that the association between CMI and OAB was stronger in women aged 20-50 years as well as in women without hypertension. Sensitivity analysis confirmed the robustness of our result.

CONCLUSION

CMI was significantly and positively associated with the prevalence of OAB, especially in women aged 20-50 years without hypertension. This finding provides a new perspective on metabolic risk management and may contribute to the early prevention and improvement of bladder function in women.

Association between cardiometabolic index and risk of testosterone deficiency in adult men: a cross-sectional study

BACKGROUND

Metabolic health is closely related to testosterone levels, and the cardiometabolic index (CMI) is a novel metabolic evaluation metric that encompasses obesity and lipid metabolism. However, there is currently a lack of research on the relationship between CMI and testosterone, which is the objective of this study.

METHODS

This study utilized data from the National Health and Nutrition Examination Survey (NHANES) cycles from 2011 to 2016. Only adult males who completed physical measurements, lipid metabolism assessments, and testosterone measurements were included in the final analysis. The exposure variable CMI was analyzed both as a continuous variable and a categorical variable divided into quartiles. Testosterone was measured using the isotope dilution liquid chromatography-tandem mass spectrometry technique. Linear and logistic regression analyses were used to explore the relationship between CMI and total testosterone (TT) levels, as well as the risk of testosterone deficiency (TD). Smooth curve fittings were employed to visualize their linear relationships. Subgroup analyses were conducted to evaluate the stability of our results across different participant characteristics. Finally, ROC analysis was used to assess the performance of CMI in predicting TD.

RESULTS

A total of 2,747 participants were included in the analysis, including 552 with TD (20.10%). The average CMI of the sample was 1.59 ± 0.03, with TD participants having a higher CMI of 2.18 ± 0.08 compared to non-TD participants at 1.46 ± 0.03. Corresponding testosterone levels were 223.79 ± 3.69 ng/dL and 508.36 ± 5.73 ng/dL, respectively. After adjusting for all covariates, participants with higher CMI showed lower TT (β = -23.84, 95% CI: -33.94, -13.74, p < 0.0001) and a higher risk of TD (OR = 1.26, 95% CI: 1.08, 1.48, p = 0.01). When CMI was categorized into quartiles with Q1 as the reference, participants in Q4 exhibited significantly lower TT (β = -74.04, 95% CI: -106.01, -42.08, p < 0.0001) and a higher risk of TD (OR = 2.34, 95% CI: 1.18, 4.64, p = 0.02). Smooth curve fittings indicated a linear relationship between these variables. Subgroup analyses confirmed the stability of these associations across different population characteristics. ROC curve analysis demonstrated that CMI had good predictive performance for TD with a cut-off value of 1.126 and an AUC (95% CI) of 0.673 (0.649, 0.700).

CONCLUSION

CMI is associated with lower TT and a higher risk of TD, and it can predict the risk of TD. Using CMI for early detection and timely intervention could reduce the disease burden and promote reproductive health. Further prospective studies with large sample sizes are needed to validate these findings.

Association between cardiometabolic index and all-cause and cause-specific mortality among the general population: NHANES 1999-2018

BACKGROUND

Cardiometabolic index (CMI) is a comprehensive clinical parameter which integrates overweight and abnormal lipid metabolism. However, its relationship with all-cause, cardiovascular disease (CVD), and cancer mortality is still obscure. Thus, a large-scale cohort study was conducted to illustrate the causal relation between CMI and CVD, cancer, and all-cause mortality among the common American population.

METHODS

Our research was performed on the basis of National Health and Nutrition Examination Survey (NHANES) database, involving 40,275 participants ranging from 1999 to 2018. The formula of CMI is [waist circumference (cm) / height (cm)] × [triglyceride (mg/dL) / high-density lipoprotein cholesterol (mg/dL)]. Outcome variables consisted of CVD, cancer, and all-cause mortality, which were identified by the International Classification of Diseases (ICD)-10. The correlation between CMI and mortality outcomes was analyzed utilizing the Kaplan-Meier survival modeling, univariate/multivariate Cox regression analysis, smooth curve fitting analysis, threshold effect analysis, and subgroup analysis. Stratification factors for subgroups included age, race/ethnicity, sex, smoking behavior, drinking behavior, BMI, hypertension, and diabetes.

RESULTS

The baseline characteristics table includes 4,569 all-cause-induced death cases, 1,113 CVD-induced death cases, and 1,066 cancer-induced death cases. Without adjustment for potential covariates, significantly positive causal correlation existed between CMI and all-cause mortality (HR = 1.03, 95% CI 1.02,1.04, P-value<0.05), CVD mortality (HR = 1.04, 95% CI 1.03, 1.05, P-value<0.05) and cancer mortality(HR = 1.03, 95% CI 1.02, 1.05, P-value<0.05); whereas, after confounding factors were completely adjusted, the relationship lost statistical significance in CMI subgroups (P for trend>0.05). Subgroup analysis found no specific subgroups. Under a fully adjusted model, a threshold effect analysis was performed combined with smooth curve fitting, and the findings suggested an L-shaped nonlinear association within CMI and all-cause mortality (the Inflection point was 0.98); in particular, when the baseline CMI was below 0.98, there existed a negative correlation with all-cause mortality with significance (HR 0.59, 95% CI 0.43, 0.82, P-value<0.05). A nonlinear relation was observed between CMI and CVD mortality. Whereas, the correlation between CMI and cancer mortality was linear.

CONCLUSIONS

Among the general American population, baseline CMI levels exhibited an L-shaped nonlinear relationship with all-cause mortality, and the threshold value was 0.98. What's more, CMI may become an effective indicator for CVD, cancer, and all-cause mortality prediction. Further investigation is essential to confirm our findings.

Association between cardiometabolic index and biological aging in the US population: evidence from NHANES 2015-2020

Purpose

It is crucial to identify biomarkers that influence the aging process and associated health risks, given the growing severity of the global population aging issue. The objectives of our research were to evaluate cardiac metabolic index (CMI) as a novel biomarker for identifying individuals at increased risk of accelerated biological aging and to assess its use in guiding preventive strategies for aging-related health risks.

Methods

The National Health and Nutrition Examination Survey (NHANES) provided cross-sectional data on participants with complete information on CMI, phenotypic age (PA), and other variables. Analyses of variance and weighted χ2 tests were conducted to assess differences between groups. The relationship between CMI and biological aging was investigated using a weighted multivariate logistic regression model, restricted cubic spline (RCS) regression analysis, subgroup analysis, and interaction testing.

Results

A positive correlation between CMI and biological aging was observed in 6,272 participants. RCS regression analysis confirmed the non-linear relationship, identifying significant inflection point at 1.10. In the crude or adjusted models, the OR (95% CI), for the highest group versus the reference were 3.608 (3.108, 4.188), 3.397 (2.920, 3.952), and 1.550 (1.299, 1.850), respectively, when categorizing CMI into different groups. Subgroup analyses and interaction tests indicate that the association between CMI and biological aging remained consistent across different subgroups. Gender, race, education level, marital status, poverty income ratio (PIR), drinking status and diabetes had an interaction with CMI in relation to biological aging.

Conclusion

An elevated CMI is linked to increased risk for biological aging. This relationship may inform more effective prevention and treatment strategies for biological aging in the future. CMI be integrated into routine health screenings or aging assessments by healthcare professionals.

Association between periodontitis and cardiometabolic index (CMI): a study from NHANES 2009-2014

Cardiometabolic index (CMI) is a novel anthropometric metric that integrates lipid and adiposity characteristics. The correlation between periodontitis development and CMI is ambiguous. The objective of this study was to establish the association between CMI and periodontitis by analyzing data from the NHANES (National Health and Nutrition Examination Survey) database. A cross-sectional study was conducted on a cohort of 6188 people selected from the NHANES database, covering the period from 2009 to 2014. The study employed multivariate logistic regression to examine the independent correlation between CMI and periodontitis. Subgroup data were analyzed and interaction tests were conducted to assess the impact of variables on the correlation between CMI and periodontitis. The CMI index was significantly and positively associated with the presence of periodontitis (β = 0.03, 95%CI(0.01, 0.05), p = 0.0092). In addition, a U-shaped relationship was found between CMI index and periodontitis severity in an older American population (65 < = age < = 80, with a folding point of 1.44, p = 0.008). This study demonstrates a significant correlation between CMI and periodontitis, positioning CMI as a crucial indicator for assessing periodontal health. Future efforts should prioritize oral hygiene interventions for patients with elevated CMI levels to facilitate early intervention and enhance overall health outcomes.

Cardiometabolic Index and chronic obstructive pulmonary disease: A population-based cross-sectional study

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death worldwide and constitutes a global health problem. The cardiometabolic index (CMI) is a new metric that combines abdominal obesity and lipid levels. Studies have shown that the prevalence of lipid metabolism disorders is greater among COPD patients and that the CMI can help reveal the potential role of lipid metabolism in disease progression by assessing the body's metabolic status; however, the association between the CMI and COPD is not known.

OBJECTIVE

To explore the association between the CMI and the prevalence of COPD.

METHODS

A cross-sectional study was conducted with 14,340 participants aged ≥ 20 years from the 2007-2018 NHANES databases. To assess the relationship between the CMI and the odds of COPD prevalence, we performed multivariate logistic regression analyses, subgroup analysis interaction tests, smoothed curve fitting, and threshold effect analyses.

RESULTS

The study included a total of 14,340 participants, 48.49 % male and 51.51 % female, and the average age was 49.75 ± 17.49 years. According to the regression model adjusted for all confounding variables, participants in the highest quartile of the CMI had 22 % greater odds of having COPD than did those in the lowest quartile (OR = 1.22, 95 % CI: 1.03, 1.21, p = 0.010). A nonlinear association was found between the CMI and COPD, with an inflection point of 0.26. The OR (95 % CI) before the inflection point was 1.27 (1.12, 1.44), p = 0.0002. The interaction was statistically significant only in the sex analysis.

CONCLUSIONS

The level of the CMI and the odds of COPD prevalence were positively correlated in our study. These findings suggest that managing abdominal obesity and lipid levels may help prevent or mitigate COPD, emphasizing the potential value of the CMI as an indicator for early intervention and precision therapy.

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.

The Different Predictive Effects of Multiple Body Fat Indexes on Metabolic Dysfunction-Associated Fatty Liver Disease

Purpose

The aim of this study was to comprehensively compare the predictive effect of 10 body fat indexes on MAFLD in different sex, age and BMI subgroups.

Patients and Methods

A total of 5403 physical examination data were included and divided into the MAFLD group (N=2632) and non-MAFLD group (N=2771). The differences and correlation of 10 promising indicators between the two groups were compared, including fatty liver index (FLI), hepatic steatosis index (HSI), lipid accumulation product (LAP), visceral fat index (VAI), cardiometabolic index (CMI), body adiposity index (BAI), and triglyceride-glucose index (TyG), waist circumference index (WC), body mass index (BMI), waist to height ratio (WHtR). Logistic regression was used to analyze the risk of MAFLD under different adjustment conditions. The operating characteristic curve of different genders, BMI levels and age subgroups was plotted.

Results

Male gender, smoking, alcohol drinking, and higher age are risk factors for MAFLD. In addition to BAI, the other 9 indicators had a high correlation with MAFLD, the area under the curve (AUC) value was >0.7, and the prediction effect was better in females, BMI<24 kg/m2, age <35 years subgroup, among which FLI (AUC: 0.912, 95% CI: 0.905-0.920), LAP (AUC: 0.894, 95% CI: 0.8866-0.903), and HSI (AUC: 0.881, 95% CI: 0.872-0.890) have better prediction effects.

Conclusion

Our study confirmed the accuracy of body fat-related indexes in predicting MAFLD in people of different sexes, ages, and BMI levels. Among them, FLI, LAP and HSI have high predictive value and can be utilized as simple and cost-effective tools for screening MAFLD in clinical settings.

Associations of cardiometabolic index with diabetic statuses and insulin resistance: the mediating role of inflammation-related indicators

BACKGROUND

This study aimed to analyze the associations of cardiometabolic index (CMI) with diabetic statuses and insulin resistance (IR) using data from the National Health and Nutrition Examination Survey (NHANES) and examined the potential mediating role of inflammation in these correlations.

METHODS

This study enrolled 9477 participants across four NHANES cycles from 2011 to 2018. The primary outcomes of the study included the risk of having prediabetes, diabetes and the level of the homeostasis model assessment of IR (HOMA-IR). Other outcomes including the levels of fasting blood glucose (FBG), hemoglobin A1c (HbA1c), oral glucose tolerance test (OGTT) results, fasting insulin, the risk of oral hypoglycemic medicine use, insulin use, and retinopathy were also collected and analyzed. Logistic regression model, subgroup analysis, restricted cubic spine (RCS), and Pearson correlation coefficients were conducted to assess the associations of CMI with diabetic statuses and IR. The mediating role of inflammation was evaluated to investigate the potential mechanism of the associations between CMI and diabetic statuses.

RESULTS

Among included participants, the CMI levels in normal participants, prediabetes and diabetes in this study were 0.48, 0.73 and 1.07. After multivariable adjustment, CMI was positively associated with the risk of prediabetes (OR = 1.49, 95% CI = 1.24-1.79), diabetes (OR = 2.14, 95% CI = 1.82-2.50) and the level of HOMA-IR (β = 2.57, 95% CI = 2.14-3.01). Besides, an increased CMI was correlated with higher levels of FBG, HBA1c, OGTT results and fasting insulin as well as the greater risk of oral hypoglycemic medicine use and insulin use. The RCS showed an inverted L-shaped association of CMI with prediabetes and diabetes (P for non-linearity < 0.001). According to Pearson correlation coefficients, higher CMI was linked to higher rises in HOMA-IR (r = 0.224, P < 0.001). Inflammation-related indicators including leukocyte and neutrophil demonstrated significant mediating effects in the associations of CMI with prediabetes (15.5%, 9.8%), diabetes (5.1%, 6.0%) and HOMA-IR (3.3%, 2.6%).

CONCLUSION

CMI was positively associated with the risk of worse diabetic statuses and higher level of IR while the associations may be partially mediated by inflammation-related indicators, suggesting that CMI could be a promising indicator for the prediction of severe diabetes and IR.

Association between the cardiometabolic index and osteoporosis: a cross-sectional study of the NHANES

Background

The cardiometabolic index (CMI) is a novel metabolic biomarker, but research on its association with osteporosis (OP) is limited. The objective of this research was to clarify the relationship between CMI and OP in the older adult population of the United States.

Methods

This study conducted a cross-sectional analysis using NHANES data 2007-2018 with exclusion of 2011-2012 and 2015-2016 cycles. Logistic regression was used to investigate the relationship between CMI and OP prevalence. Restricted cubic spline curve (RCS) and threshold saturation analyses were performed to explore the nonlinear association between CMI and OP prevalence. Subgroup analyses, sensitivity analyses, and additional analyses were conducted to ensure the robustness and reliability of the findings.

Results

The study included 4,191 participants, revealing that those with OP had significantly lower CMI levels. Logistic regression revealed a strong inverse correlation between Log CMI and OP (OR = 0.72, 95% CI = 0.59-0.88), which persisted after adjusting for covariates. RCS analysis revealed a nonlinear inverse relationship with the critical threshold at CMI = 0.93. Below this threshold, each unit increase in CMI was associated with a 37% reduction in OP prevalence, but changes above this threshold were not significant. Subgroup and sensitivity analyses confirmed the robustness of the findings.

Conclusion

Elevated CMI exhibited a robust inverse correlation with the prevalence of OP in the older adult U.S. population. Maintaining a moderate CMI significantly diminishes the risk of developing OP.

Characteristics of Different Obesity Metabolic Indexes and their Correlation with Insulin Resistance in Patients with Polycystic Ovary Syndrome

This study is aimed to investigate the characteristics of different obesity metabolic indexes [body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), and lipid aggregation products (LAP)] and their correlation with insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS). The study was conducted on 140 subjects with PCOS and 133 control subjects aged 18-44 years. According to insulin resistance index (HOMA-IR) ≥ 2.69 and HOMA-IR < 2.69, PCOS group members were divided into insulin resistance group and non-insulin resistance group. Anthropometric and serological characteristics of the population with PCOS focused on calculating different obesity metabolic indexes and HOMA-IR. BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher in PCOS patients than in the control group, and the differences were all statistically significant (P < 0.05); In the insulin resistance group of PCOS patients, BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher than in the non-insulin resistance group (P < 0.05). In PCOS patients, BMI (r = 0.658, P < 0.001), WC (r = 0.0.662, P < 0.001), WHR (r = 0.377, P < 0.001), WHtR (r = 0.660, P < 0.001), CMI (r = 0.698, P < 0.001), BRI (r = 0.757, P < 0.001), VAI (r = 0.640, P < 0.001), and LAP (r = 0.767, P < 0.001) were positively correlated with IR. Obesity metabolic indexes associated with PCOS were elevated in the PCOS group compared to the control group, and in the PCOS insulin-resistant group compared to the non-insulin resistant group. Novel obesity metabolic indexes, especially CMI, BRI and LAP, might be more appropriate for evaluating the risk of concurrent IR in PCOS.

Unraveling the Interaction between Inflammation and the Cardiometabolic Index in Older Men: A Pilot Study

Both cardiometabolic and chronic inflammatory diseases pose a significant challenge to global public health, particularly among older adults. Here, we investigated the interplay between systemic inflammatory status and the cardiometabolic index (CMI) in older men with adequate weight or obesity. In this observational cross-sectional study, older men (71.79 ± 7.35 years) were separated into groups with normal weight (NW, n = 34) and obesity (O, n = 32) to assess circulating levels of pro- and anti-inflammatory cytokines and CMI. Overall, the O group showed not only a higher inflammatory status but also increased CMI (p < 0.0001) compared with the NW group. Interestingly, only positive correlations were found between pro- and anti-inflammatory cytokines in both groups. Through multivariate regression analysis, IL-6 (β = -0.2276, p = 0.0003) and IL-10 (β = 0.2023, p = 0.0030) significantly influenced CMI in the NW group. No significant results were found in the O group. Our findings reinforce the effects of obesity in inflammaging, as well as suggesting that the influence of cytokines in CMI occurs in older men with normal weight, since the elevated pro-inflammatory profile observed in older men with obesity can interfere in this effect.

Association of cardiometabolic and triglyceride-glucose index with left ventricular diastolic function in asymptomatic individuals

BACKGROUND AND AIMS

Obesity and insulin resistance are associated with left ventricular diastolic dysfunction (LVDD) and increased risk of heart failure. Cardiometabolic index (CMI) and triglyceride glucose (TyG) are new indexes to assess visceral obesity and insulin resistance, respectively. The study aimed to investigate the clinical usefulness of these indexes for identifying LVDD individuals.

METHODS AND RESULTS

Overall, 1898 asymptomatic individuals were included in this cross-sectional study. Participants underwent anthropometrics, serum biochemical evaluation, and echocardiography. Multiple linear regression analysis revealed that both indexes were independent determinants of diastolic parameters among females; while for males, CMI and TyG were not associated with A velocity. In the multivariate logistic analysis, the proportion of LVDD in the third and fourth quartiles of CMI remained significantly greater than that in the lowest quartile in females (Q3 vs. Q1: odds ratio (OR) = 2.032, 95% confidence interval (CI): 1.181-3.496; Q4 vs. Q1: OR = 2.393, 95% CI: 1.347-4.249); while in males, the incidence of LVDD was significantly greater only in the fourth quartile. For TyG, the presence of LVDD in the fourth quartile was significantly greater in both genders. The discriminant values between the CMI (AUC: 0.704, 95% CI: 0.668-0.739) and TyG (AUC: 0.717, 95% CI: 0.682-0.752) were similar in females. Both indexes performed better in females than in males to identify LVDD.

CONCLUSION

The CMI and TyG might both serve as effective tools to identify LVDD in routine health check-ups in primary care, mainly in females. With simpler parameters, the CMI could be utilized in medically resource-limited areas.

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.

Novel anthropometric indicators of visceral obesity predict the severity of hyperlipidemic acute pancreatitis

BACKGROUND

Obesity substantially contributes to the onset of acute pancreatitis (AP) and influences its progression to severe AP. Although body mass index (BMI) is a widely used anthropometric parameter, it fails to delineate the distribution pattern of adipose tissue. To circumvent this shortcoming, the predictive efficacies of novel anthropometric indicators of visceral obesity, such as lipid accumulation products (LAP), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), A Body Shape Index (ABSI), and Chinese visceral adiposity index (CVAI) were examined to assess the severity of AP.

METHOD

The body parameters and laboratory indices of 283 patients with hyperlipidemic acute pancreatitis (HLAP) were retrospectively analysed, and the six novel anthropometric indicators of visceral obesity were calculated. The severity of HLAP was determined using the revised Atlanta classification. The correlation between the six indicators and HLAP severity was evaluated, and the predictive efficacy of the indicators was assessed using area under the curve (AUC). The differences in diagnostic values of the six indicators were also compared using the DeLong test.

RESULTS

Patients with moderate to severe AP had higher VAI, CMI, and LAP than patients with mild AP (all P < 0.001). The highest AUC in predicting HLAP severity was observed for VAI, with a value of 0.733 and 95% confidence interval of 0.678-0.784.

CONCLUSIONS

This study demonstrated significant correlations between HLAP severity and VAI, CMI, and LAP indicators. These indicators, particularly VAI, which displayed the highest predictive power, were instrumental in forecasting and evaluating the severity of HLAP.

Association between cardiometabolic index and depression: National Health and Nutrition Examination Survey (NHANES) 2011-2014

BACKGROUND

Emerging evidence suggests a common pathophysiological basis for metabolic disorders and mental diseases. Despite the existence of reports suggesting a strong connection between dyslipidemia and depression, a comprehensive and reliable indicator to identify depression is still lacking. Cardiometabolic index (CMI) is an integrated index calculated from three vital metabolic indicators, including triglyceride (TG), high-density lipoprotein cholesterol (HDLC) and waist height ratio (WHtR).

OBJECTIVE

This study aims to explore the association between CMI and depression.

METHODS

Cross-sectional data of participants with complete information of CMI, depression, and other covariates were obtained from the National Health and Nutrition Examination Survey (NHANES). Weighted student's t-test and Chi-square test were used to identify the differences between two groups. Weighted multivariate logistic regression model, restricted cubic spline (RCS) regression analysis, subgroup analysis and interaction tests were conducted to explore the association between CMI and depression. Receiver operating curve (ROC) analysis and area under the curve (AUC) were also utilized to evaluate the performance of CMI in identifying depression.

RESULTS

A positive correlation between CMI and depression was observed in 3794 participants included in the study, which was further confirmed to be non-linear via RCS regression analysis, with two significant inflection points being identified, including 0.9522 and 1.58. In the crude or adjusted models, individuals with a CMI level ≥ 0.9522 exhibited remarkably increased risk for developing depression. CMI got an AUC of 0.748 in identifying depression. Subgroup analyses and interaction tests indicate that the association between CMI and depression remained consistent across different subgroups and was not modified by other covariates except drinking. Those who are current drinkers and with a high CMI are more susceptible to suffer depression.

CONCLUSIONS

An elevated CMI is linked to increased risk for depression. Addressing dyslipidemia and improving lipid levels may potentially lower the risk for depression.

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.

Application Value of Cardiometabolic Index for the Screening of Obstructive Sleep Apnea with or Without Metabolic Syndrome

Background

Obstructive sleep apnea (OSA) is a common chronic disease with various comorbidities. The cardiometabolic index (CMI) reflects visceral fat tissue distribution and function, assessing the risk of obesity-related conditions such as metabolic syndrome (MetS) and stroke, which are strongly connected to OSA. The relationship between CMI with OSA and OSA combined with MetS (OMS) remains unclear. This study aims to evaluate the screening value of CMI for OSA and OMS, compared to the lipid accumulation product (LAP).

Methods

A total of 280 participants who underwent polysomnography were finally included, with the measurements of metabolic-related laboratory test results such as total cholesterol and triglyceride. Receiver operating curve (ROC) analysis and calculation of the area under the curve (AUC) were conducted to assess the screening potential of CMI, LAP, and the logistic regression models established based on them for OSA and OMS. The Youden index, sensitivity, and specificity were used to determine the optimal cutoff points.

Results

ROC curve analysis revealed that the AUCs for CMI in screening OSA and OMS were 0.808 and 0.797, and the optimal cutoff values were 0.71 (sensitivity 0.797, specificity 0.776) and 0.89 (sensitivity 0.830, specificity 0.662), respectively, showing higher Youden index than LAP. The AUCs of screening models based on CMI for OSA and OMS were 0.887 and 0.824, respectively.

Conclusion

CMI and LAP can effectively screen for OSA and OMS, while CMI has more practical cutoff values for identifying the diseased states. Screening models based on CMI demonstrate a high discriminatory ability for OSA and OMS, which needs verification in a large-scale population.

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.

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.

Associations between body composition profile and hypertension in different fatty liver phenotypes

Background

It is currently unclear whether and how the association between body composition and hypertension varies based on the presence and severity of fatty liver disease (FLD).

Methods

FLD was diagnosed using ultrasonography among 6,358 participants. The association between body composition and hypertension was analyzed separately in the whole population, as well as in subgroups of non-FLD, mild FLD, and moderate/severe FLD populations, respectively. The mediation effect of FLD in their association was explored.

Results

Fat-related anthropometric measurements and lipid metabolism indicators were positively associated with hypertension in both the whole population and the non-FLD subgroup. The strength of this association was slightly reduced in the mild FLD subgroup. Notably, only waist-to-hip ratio and waist-to-height ratio showed significant associations with hypertension in the moderate/severe FLD subgroup. Furthermore, FLD accounted for 17.26% to 38.90% of the association between multiple body composition indicators and the risk of hypertension.

Conclusions

The association between body composition and hypertension becomes gradually weaker as FLD becomes more severe. FLD plays a significant mediating role in their association.

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.

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.

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 Differences in the TyG Index and Cardiovascular Risk Factors in Metabolically Obese Normal Weight Phenotype

BACKGROUND

The triglyceride glucose (TyG) index is a novel surrogate marker of insulin resistance and increases cardiovascular disease risk. We sought to explore sex differences in the relationship between TyG and cardiovascular (CV) risk factors in metabolically obese normal weight (MONW) phenotype.

METHOD

We analyzed data of 1208 healthy men and nonpregnant women enrolled in a population-based longitudinal study from January 2017-June 2020. MONW phenotype was defined by normal body mass index (BMI: 18-<25 kg/m2) with at least one of the following metabolic disorders (MONW phenotype): elevated blood pressure (BP), hypertriglyceridemia, hyperglycemia, and low HDL cholesterol. Multiple logistic regression analysis was performed to assess the association between elevated TyG index and the CV risk factors in women and men and was presented in odds ratio (OR) with 95% confidence interval (CI).

RESULTS

Of 1208 subjects, 350 (29%) were MONW phenotype (mean age (years): male: 43.5 ± 12.4 and female: 43.1 ± 12.7) and 858 were metabolically healthy normal weight (MHNW; n = 858 (71%)). MONW women had higher mean values of the TyG index (8.03 ± 5.07) than men (7.47 ± 4.68). Multivariate analysis revealed that the elevated TyG index is significantly associated with MONW phenotype in women (adjusted OR: 8.73, 95% CI: 5.62-13.57) and men (aOR: 5.90, 95% CI: 4.23-8.23). TyG was found to be an excellent predictor of MONW status in both women (receiver operating characteristic (ROC) area under the curve (AUC): 0.979, 95% CI: 0.969-0.988) and men (ROC-AUC: 0.968, 95% CI: 0.952-0.983).

CONCLUSION

Our study revealed that the TyG index may represent a cost-effective and informative screening tool for the high-risk MONW phenotype.

Metabolic Obesity in People with Normal Body Weight (MONW)-Review of Diagnostic Criteria

Disorders of metabolic obesity with normal body weight (MONW) are widely recognized risk factors for the development of cardiovascular diseases and type 2 diabetes. Despite this, MONW is not diagnosed in clinical practice. There is no consensus on the definition of MONW, and measuring the degree of insulin resistance or obesity among apparently healthy, non-obese patients is not widely applicable. The awareness of the relationship between metabolic disorders such as MONW and a higher risk of mortality from cardiovascular causes and other related diseases prompts the need for action to be taken aimed at creating appropriate diagnostic models that will allow for the effective detection of those with metabolic abnormalities among people with normal body weight. Such actions are decisive in the prevention and treatment of diseases. Therefore, the purpose of this article is to review the MONW diagnostic criteria used over the years.

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.