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

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.

Cardiometabolic index and mortality risks: elevated cancer and reduced cardiovascular mortality risk in a large cohort

BACKGROUND

With metabolic disorders on the rise globally, the cardiometabolic index (CMI) has emerged as a crucial predictor of mortality risks linked to cancer, cardiovascular disease, and diabetes. This novel index, which combines lipid metabolism and body composition, is the focus of this study, aimed at exploring its association with all-cause and specific mortality in an all-age adult population.

METHODS

A longitudinal cohort study including 5,728 participants aged over 18 from nine cycles between 2001 and 2018 was enrolled and assessed. CMI served as the exposure variable, while outcomes included all-cause mortality and mortality due to cardiovascular disease, cancer, and diabetes. The Cox frailty model and average marginal effects were employed to evaluate the contribution of CMI to all-cause and specific mortality collectively. Restricted cubic spline analyses and stratified analyses were conducted to investigate potential nonlinear effects and interactions.

RESULTS

The decreased participants exhibited considerably higher CMI than the alive's. A positive association was found between CMI and all-cause mortality (HR=1.05, 95% CI=1.01-1.10). Notably, CMI was linked to an increased risk of cancer mortality (HR=1.02) and a reduced risk of cardiovascular disease mortality (HR=0.85). Furthermore, the average marginal effect of CMI on diabetes mortality was the largest (AME=0.499). The RCS curves revealed that participants had the lowest risk of all-cause mortality at a CMI of 0.618. Sensitivity analyses further supported these findings.

CONCLUSION

This study represents the first comprehensive assessment on the contribution of CMI to mortality across an all-age adult population, providing some insights for the comprehensive assessment of health and disease states.

The relationship between composite lipid indices and baveno classification in patients with obstructive sleep apnoea

Obstructive Sleep Apnoea (OSA) is associated with the development of cardiovascular disease (CVD); however, the risk is only weekly related to OSA severity traditionally determined by the apnoea-hypopnoea index. The Baveno classification was developed to improve patient selection who would benefit from OSA treatment in terms of symptoms improvement and CVD risk reduction. However, it is unclear how the classification relates to biomarkers of CVD risk. Composite lipid indices were evaluated in various populations and showed good predictive value for incident CVD. One thousand two hundred and forty-two patients with OSA were included in the study. Composite lipid indices, including the atherogenic index of plasma (AIP), visceral adiposity index (VAI), lipid accumulation product (LAP) and cardiometabolic index (CMI) were compared between different Baveno groups (A - minor symptoms, minor comorbidities, B - severe symptoms, minor comorbidities, C - minor symptoms, severe comorbidities, D - severe symptoms, severe comorbidities). All composite lipid indices were higher in group D versus groups A and C. Only LAP (86.93 /58.40-119.49/ vs. 75.73 /48.37-99.04/) and CMI (1.03 /0.69-1.42/ vs. 0.91 /0.63-1.12/) were significantly different between the minimally symptomatic groups (C vs. A), and solely LAP was significantly higher (110.69 /76.76-147.22/ vs. 82.32 /60.35-113.50/) when the highly symptomatic groups (D vs. B) were compared. The Baveno classification correlates with cardiovascular risk estimated with composite lipid indices. Composite lipid indices may help better stratifying cardiovascular risk in both minimally- and highly symptomatic patients.

Association of cardiometabolic index with sleep quality in adults: a population‑based study

The Cardiometabolic Index (CMI) represents an innovative metric that encompasses abdominal obesity and lipid levels, offering a comprehensive assessment of cardiometabolic health. It is derived through the multiplication of the waist-to-height ratio by the triglyceride-to-high-density lipoprotein cholesterol ratio. Although obesity and blood lipid levels are known factors affecting sleep quality, the direct correlation between CMI and sleep quality has yet to be elucidated. This study uses NHANES data to explore the potential correlation between CMI and sleep quality. Our research employed a cross-sectional design, utilizing data from the National Health and Nutrition Examination Survey (NHANES) spanning 2011 to 2014. CMI was used as the exposure variable, with sleep quality assessed through three self-reported measures: trouble sleeping, sleep disorders, and sleep duration. We employed multivariate logistic regression models and linear regression model as well as subgroup analyses to explore the independent relationship between CMI and sleep quality. Additionally, interaction tests were conducted to examine differences across various subgroups. The study included 4298 participants, comprising 2134 males and 2164 females. There was a positive correlation between CMI and trouble sleeping (OR = 1.63, 95% CI 1.28-2.08) and sleep disorders (OR = 1.96, 95% CI 1.43-2.67), while there was a negative correlation between CMI and sleep duration (β = - 0.17, 95% CI - 0.31 to - 0.03), indicating that a higher CMI was associated with shorter sleep duration. Subgroup analyses and interaction tests revealed a consistently positive association between CMI and sleep difficulty across various populations, including gender, age, hypertension, diabetes, and cardiovascular disease history. However, the relationship between CMI and sleep disorders was more prominent among participants aged 50 and above. In American adults, a higher CMI is linked to an increased prevalence of sleep disturbances. In clinical practice, CMI can be considered as a supplementary factor in the assessment and management of sleep problems. Our study also provided new insights for improving sleep quality.

Association between obstructive sleep apnea and visceral adiposity index and lipid accumulation product: NHANES 2015-2018

BACKGROUND

Obesity refers to a significant contributor to the development of obstructive sleep apnea (OSA). Early prediction of OSA usually leads to better treatment outcomes, and this study aims to employ novel metabolic markers, visceral adiposity index (VAI), and lipid accumulation product (LAP) to evaluate the relationship to OSA.

METHODS

The data used in the current cross-sectional investigation are from the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2015 and 2018. To examine the correlation between LAP and VAI levels and OSA, multivariate logistic regression analysis was adopted. In addition, various analytical methods were applied, including subgroup analysis, smooth curve fitting, and threshold effect analysis.

RESULTS

Among totally 3932 participants, 1934 were included in the OSA group. The median (Q1-Q3) values of LAP and VAI for the participants were 40.25 (21.51-68.26) and 1.27 (0.75-2.21), respectively. Logistic regression studies indicated a positive correlation between LAP, VAI, and OSA risk after adjusting for potential confounding variables. Subgroup analysis revealed a stronger correlation between LAP, VAI levels, and OSA among individuals aged < 60 years. Through smooth curve fitting, specific saturation effects of LAP, VAI, and BMD were identified, with inflection points at 65.684 and 0.428, respectively.

CONCLUSION

This study demonstrates that elevated levels of LAP and VAI increase the risk of OSA, suggesting their potential as predictive markers for OSA and advocating for dietary and exercise interventions to mitigate OSA risk in individuals with high LAP and VAI levels.