BACKGROUND: Previous findings have revealed that disorders of lipid metabolism may be a risk factor for pulmonary function damage; however, the combined effect of dyslipidemia and central obesity on pulmonary function is unclear. The cardiometabolic index (CMI) is a composite of serum lipids (triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C)) and visceral fat parameters (waist-to-height ratio (WHtR)). This research aimed to investigate the link between CMI and pulmonary function, employing large-scale demographic data sourced from the National Health and Nutrition Examination Survey (NHANES) database.
METHODS: This cross-sectional study used data involving 4125 adults aged 20 and above collected by NHANES between 2007 and 2012. We defined CMI as the exposure variable and measured outcomes using forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC to evaluate pulmonary function. Weighted multiple linear regression models and subgroup analyses were employed to investigate separate relationships between CMI and pulmonary function. In addition, to investigate variations across different strata and evaluate the robustness of the findings, interaction tests and sensitivity analyses were conducted.
RESULTS: Results from the weighted multiple linear regression analysis indicated a unit increase in log2-CMI was associated with a reduction of 82.63 mL in FEV1 and 112.92 mL in FVC. The negative association remained significant after transforming log2-CMI by quartile (Q). When the log2-CMI level reached Q4, β coefficients (β) were -128.49 (95% CI: -205.85, -51.13), -169.01 (95% CI: -266.72, -71.30), respectively. According to the interaction test findings, the negative association linking log2-CMI with FEV1 and FVC persists regardless of confounding factors including age, gender, BMI, physical activity (PA), and smoking status. A subsequent sensitivity analysis provided additional confirmation of the stability and reliability of the results. For females, the inflection points for the nonlinear relationships between log2-CMI and FEV1, as well as log2-CMI and FVC, were identified at 2.33 and 2.11, respectively. While in males, a consistent negative association was observed.
CONCLUSIONS: Our findings suggest that higher CMI is associated with lower FEV1 and FVC. CMI may serve as a complementary consideration to the assessment and management of pulmonary function in clinical practice.

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.

UNASSIGNED: Cardiometabolic Index (CMI) is a surrogate marker for metabolic disorders. It is associated with various chronic diseases. This study aims to investigate the relationship between CMI and asthma.
UNASSIGNED: Data from seven consecutive National Health and Nutrition Examination Survey cycles between 2005 and 2018 were used. The study included adults with self-reported asthma diagnoses and complete information for CMI calculation. The formula for CMI is CMI = [WC (cm)/height (cm)] × [TG (mg/dL)/HDL-C (mg/dL)]. A multivariate logistic regression model was employed to examine the linear relationship between CMI and asthma. Subgroup analyses were conducted to explore potential influencing factors. Additionally, smooth curve fitting and threshold effect analysis were used to describe the non-linear relationship.
UNASSIGNED: A higher CMI was possibly associated with an increased prevalence of asthma. After adjusting for various covariates including marital status, Poverty Income Ratio, Body Mass Index, hypertension, diabetes, smoking, alcohol consumption, heart attack, and stroke, the results remained significant (OR = 1.03; 95%CI, 1.00-1.05, p = 0.0178, R2 = 0.52). Participants with the highest CMI had a 38% increased risk of asthma prevalence compared to those with the lowest CMI (OR = 1.38; 95%CI, 1.19-1.60, p < 0.0001).
UNASSIGNED: The findings reveal that elevated CMI levels correlate with an increased risk of asthma, highlighting CMI\'s potential as a predictive marker for asthma, particularly in populations with a CMI below 1.97. These results suggest that interventions aimed at improving metabolic health may prove effective in managing or preventing asthma.

BACKGROUND: This study sought to elucidate the associations of cardiometabolic index (CMI), as a metabolism-related index, with all-cause and cardiovascular mortality among the older population. Utilizing data from the National Health and Nutrition Examination Survey (NHANES), we further explored the potential mediating effect of inflammation within these associations.
METHODS: A cohort of 3029 participants aged over 65 years old, spanning six NHANES cycles from 2005 to 2016, was enrolled and assessed. The primary endpoints of the study included all-cause mortality and cardiovascular mortality utilizing data from National Center for Health Statistics (NCHS). Cox regression model and subgroup analysis were conducted to assess the associations of CMI with all-cause and cardiovascular mortality. The mediating effect of inflammation-related indicators including leukocyte, neutrophil, lymphocyte, systemic immune-inflammation index (SII), neutrophil to lymphocyte ratio (NLR) were evaluated to investigate the potential mechanism of the associations between CMI and mortality through mediation package in R 4.2.2.
RESULTS: The mean CMI among the enrolled participants was 0.74±0.66, with an average age of 73.28±5.50 years. After an average follow-up period of 89.20 months, there were 1,015 instances of all-cause deaths and 348 cardiovascular deaths documented. In the multivariable-adjusted model, CMI was positively related to all-cause mortality (Hazard Ratio (HR)=1.11, 95% CI=1.01-1.21). Mediation analysis indicated that leukocytes and neutrophils mediated 6.6% and 13.9% of the association of CMI with all-cause mortality.
CONCLUSIONS: Elevated CMI is positively associated with all-cause mortality in the older adults. The association appeared to be partially mediated through inflammatory pathways, indicating that CMI may serve as a valuable indicator for poor prognosis among the older population.

BACKGROUND: The cardiometabolic index (CMI) is a new type of obesity index that is based on a combination of lipid levels and abdominal obesity indicators. It is closely correlated with the occurrence of diabetes mellitus, atherosclerosis, hypertension, and other diseases, thus playing an important role in the screening of metabolic diseases. This is coupled with hepatic steatosis and fibrosis which are characterized by excessive liver fat deposition. The aim of this study was to investigate the possible association between CMI and hepatic steatosis and liver fibrosis.
METHODS: A cross-sectional investigation was conducted using the 2017-2020 National Health and Nutrition Examination Survey (NHANES) dataset to probe the relationship between CMI and hepatic steatosis and liver fibrosis, while multiple linear regression models were used to test the linear association between CMI and controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Smooth-fit curves and threshold effects analysis were used to describe the nonlinear relationships. Subgroup analyses were performed according to gender, age, body mass index (BMI), hypertension, diabetes, cardiovascular disease, and smoking status.
RESULTS: A total of 3084 adults aged 18-80 years were included in this analysis, and after controlling for a variety of variables, there was a significant positive correlation between CMI and CAP [20.38 (16.27,24.49)]. When subgroups were analyzed, this positive correlation was found to be stronger in the female population than in the male (P for interaction = 0.0303). Furthermore, the association between CMI and CAP was nonlinear. Using multiple regression analysis, it was shown that the linear relationship between CMI and liver fibrosis was not significant [-0.09 (-0.47,0.29)].
CONCLUSIONS: The findings suggest that elevated CMI levels are associated with hepatic steatosis, but that CMI is not linked to liver fibrosis. Larger prospective investigations are needed to confirm our findings.

Composed of obesity and lipid parameters, the cardiometabolic index (CMI) has emerged as a novel diagnostic tool. Originally developed for diabetes diagnosis, its application has expanded to identifying patients with cardiovascular diseases, such as atherosclerosis and hypertension. However, the relationship between CMI and non-alcoholic fatty liver disease (NAFLD) and liver fibrosis in the US population remains unclear. This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2017-2020, involving 2996 participants aged 20 years or older. Vibration controlled transient elastography using a FibroScan® system (model 502, V2 Touch) with controlled attenuation parameter measurements identified NAFLD at a threshold of ≥ 274 dB/m, while liver stiffness measurement (LSM) results (median, ≥ 8.2 kPa) indicated fibrosis. A multifactorial logistic regression model explored the relationship between CMI and NAFLD and fibrosis. The effectiveness of CMI in detecting NAFLD and liver fibrosis was assessed through receiver operating characteristic curve analysis. Controlling for potential confounders, CMI showed a significant positive association with NAFLD (adjusted OR = 1.44, 95% CI 1.44-1.45) and liver fibrosis (adjusted OR = 1.84, 95% CI 1.84-1.85). The Areas Under the Curve for predicting NAFLD and fibrosis were 0.762 (95% CI 0.745 ~ 0.779) and 0.664(95% CI 0.633 ~ 0.696), respectively, with optimal cut-off values of 0.462 and 0.527. There is a positive correlation between CMI and NAFLD and fibrosis, which is a suitable and simple predictor of NAFLD and fibrosis.

BACKGROUND: Diabetes is a significant risk factor for cognitive impairment. Therefore, early identification of cognitive impairment in diabetic patients is particularly important. The aim of this study was to assess the relationship between Cardiometabolic index (CMI) and cognitive function in a diabetic population.
METHODS: A cross-sectional study was conducted by collecting information from the National Health and Nutrition Examination Survey (NHANES) 2011-2014. Multiple linear regression models were used to investigate the correlation between CMI and low cognitive function in a diabetic population. Threshold effects analysis and fitted smoothing curves were used to describe the nonlinear links. Interaction tests and subgroup analyses were also performed.
RESULTS: A total of 1,050 people participated in this study, including 561 men and 489 women. In the fully corrected model, CMI was positively associated with low cognitive performance as assessed by CERAD Word List Learning Test (CERAD W-L), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) (OR = 1.37 [1.14, 1.72], p = 7.4 × 10-3), (OR = 1.21 [1.04, 1.51], p = 1.26 × 10-2), and (OR = 1.27 [1.08, 1.63], p = 2.53 × 10-2). Our study found that diabetic patients with higher CMI were at greater risk of developing low cognitive function. The effect of the subgroups on the positive association of CMI with cognitive impairment was not significant. A non-linear association between low cognitive performance and CMI was determined by CERAD W-L, AFT, and DSST (log-likelihood ratio <5 × 10-2). In addition, our also study found that CMI was a better predictor of cognitive impairment in diabetes than weight-adjusted waist index (WWI).
CONCLUSIONS: Increased CMI is associated with an increased risk of cognitive impairment in people with diabetes. CMI can be used as a new anthropometric measure for predicting cognitive impairment in diabetes, with stronger predictive power than WWI.

Background: The concomitant occurrence of obesity and metabolic syndrome (MetS) causes a significant worsening of a patient\'s clinical condition. Indexes that employ anthropometric measurements alone or associated with blood parameters have been investigated for their ability to identify MetS. This study aimed to evaluate the diagnostic accuracy of three of these indexes, the body adiposity index (BAI), the lipid accumulation product index (LAP), and the cardiometabolic index (CMI), in a cohort of 1912 adult subjects with obesity. Methods and Results: MetS was found in 62.3% of the enrolled subjects, with a higher prevalence in males (72.5%) than females (60.9%). Receiver operating characteristic (ROC) analysis was used to define which index performed better. The BAI was found to be the lowest-performing index, with an ROC area of 0.50, a sensitivity of 30.31%, a specificity of 74.48%, and a likelihood ratio of 1.19. On the contrary, the LAP and the CMI showed a comparable ROC area of 0.82. The LAP had a sensitivity of 63.06%, a specificity of 86.55%, and a likelihood ratio of 4.69, while the CMI had a sensitivity of 67.59%, specificity of 81.55%, and a likelihood ratio of 3.66. The analysis was also performed in the group divided into males and females, with overlapping results. Conclusions: The LAP and the CMI performed better than the BAI in detecting MetS both in the general population with obesity and in the male/female subgroups. In the future, it will be important to validate these useful diagnostic tools in order to employ them in clinical practices.

BACKGROUND: Cardiovascular and metabolic diseases include a large group of pathologies and constitute one of the most serious chronic health problems facing the 21st century, with high rates of morbidity and mortality worldwide. Unhealthy diets influence the development of these pathologies. The Mediterranean diet can be an important part in the treatment of these diseases. The objective of this study was to assess the effect of a program that aims to increase adherence to the Mediterranean diet on the improvement of different cardiometabolic risk parameters.
METHODS: A prospective intervention study was carried out on 7034 Spanish workers. Prior to the intervention, 22 cardiometabolic risk scales were evaluated. Participants in this study were informed both orally and in writing of the characteristics and benefits of the Mediterranean diet and were given the website of the Ministry of Health, Consumption and Social Welfare of Spain, which provides advice on nutrition. Adherence to the Mediterranean diet was reinforced by sending a monthly SMS to their mobile phones. After six months of follow-up, the 22 risk scales were re-evaluated to assess changes. Means and standard deviations were calculated using Student\'s t test to analyse quantitative variables. Prevalence was calculated using the Chi-square test when the variables were qualitative.
RESULTS: All the cardiometabolic risk scales studied decreased after implementing a program to improve and enhance adherence to the Mediterranean diet. The number of losses in the sample was very low, standing at 4.31%.
CONCLUSIONS: The Mediterranean diet is effective in reducing all cardiovascular risk scales evaluated. The mean values and prevalence of high values of the different cardiometabolic risk scales analysed led to lower values after the implementation of the program to increase adherence to the Mediterranean diet. We observed a significant positive difference in metabolic age in both sexes. We have obtained a significant improvement in the insulin resistance index, especially in the SPISE-IR index, data that we have not found in previous publications. Easy access to the Internet and new information and communication technologies facilitate adherence to a diet and can reduce the number of losses.

UNASSIGNED: Physical activity (PA) is widely recommended for preventing and combating obesity, but the most effective PA pattern for treating obesity remains unclear. Cardiometabolic index (CMI), derived from waist height ratio and triglycerides to high-density lipoprotein-cholesterol ratio, is a novel indicator for evaluating obesity. However, the relationship between different PA patterns and CMI remains unelucidated.
UNASSIGNED: This study aimed to explore the association between different PA patterns and CMI in U.S. adults.
UNASSIGNED: Participants with complete information in CMI, PA patterns, and other covariates in the National Health and Nutrition Examination Survey database (2007-2016) were included in this study. Multivariate linear regression models were utilized to explore the relationship between PA patterns and CMI. Moreover, stratified analyses, interaction tests and restricted cubic spline (RCS) regression analysis were used to investigate the stability and nonlinearity of the association, respectively.
UNASSIGNED: A total of 16,442 adults were included in this study. After adjusting for all potential covariates, only the regularly active group was significantly associated with CMI reduction (β = -0.13, 95% CI: 0.19 to -0.07, P < 0.0001), while the weekend warriors group did not achieve equivalent CMI reduction (β = -0.09, 95% CI: 0.32 to 0.14, P = 0.4204). Subgroup analyses and interaction tests revealed that the CMI-PA association was more pronounced in the subgroup with age≤45 or >60, with higher education level, and who are current drinkers. Furthermore, RCS analysis indicated that total PA in a week was significantly, nonlinearly associated with CMI in non-inactive adults, and that a total of PA more than 330 min can reap favorable CMI reduction.
UNASSIGNED: Being regularly active is associated with significant CMI reduction, while being weekend warriors and insufficiently active do not achieve equivalent benefits. For non-inactive individuals, engaging in PA for more than 330 min weekly helps to reduce CMI effectively.