Abstract
BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep-disordered breathing condition closely associated with cardiovascular and metabolic risks. The current diagnostic gold standard, polysomnography, faces accessibility limitations, necessitating the development of simplified screening tools. Integrating multi-pathway information from hematological biomarkers may offer novel approaches. OBJECTIVE: To systematically evaluate the association between multiple novel inflammatory-metabolic composite indices and OSA risk, and validate their stability across different populations. METHODS: A two-stage cross-sectional study design was employed. Stage one utilized a clinical cohort from Chengdu Third People's Hospital, China (n = 300, PSG-diagnosed), conducting preliminary analyses of seven indices: MHR, PHR, NHHR, AIP, UHR, RC/HDL, and SIRI. Phase II employed the US National Health and Nutrition Examination Survey (NHANES) database (n = 4,423, questionnaire-diagnosed) for external validation, incorporating the CMI index. Multivariate logistic regression models analyzed marker-OSA associations, with area under the ROC curve (AUC) assessing discriminatory capacity and subgroup analyses conducted. RESULTS: After adjusting for demographics, lifestyle factors, and clinical comorbidities, multiple indicators were independently associated with OSA risk. Within the clinical cohort, AIP, UHR, and RC/HDL demonstrated the most robust associations; in the NHANES cohort, CMI (AUC = 0.621), UHR (AUC = 0.613), AIP, and RC/HDL (both AUC = 0.602) exhibited favorable predictive performance. Subgroup analyses revealed that the predictive value of these markers was particularly pronounced in individuals aged≤60 years, females, non-obese individuals, and those without underlying conditions (hypertension, diabetes, cardiovascular disease). CONCLUSION: This two-phase study identified several readily available inflammatory-metabolic composite indices (e.g., MHR, AIP, CMI) as independently associated with OSA risk; these markers demonstrate potential as adjunctive tools for assessing OSA risk. Their predictive efficacy exhibits population heterogeneity, necessitating consideration of individual characteristics in clinical application. Prospective studies are required to further validate their causal associations and clinical utility.